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244 articles · Page 2 of 3
Model Perspective
Model Perspective
Nov 13, 2022 · Fundamentals

Essential Python Programming Resources: Basics, Libraries, and Modeling Tools

This article compiles a curated list of Python programming fundamentals and popular third‑party libraries for data processing, visualization, scientific computing, optimization, and more, linking to detailed tutorials for each topic, including Numpy, Matplotlib, Pandas, Scipy, PuLP, NetworkX, Geatpy, Numba, and Taichi.

LibrariesScientific Computingdata science
0 likes · 4 min read
Essential Python Programming Resources: Basics, Libraries, and Modeling Tools
Model Perspective
Model Perspective
Oct 12, 2022 · Fundamentals

Mastering Model‑Centric Statistics: From Exploratory Analysis to Bayesian Inference

This article explains how statistics—through data collection, exploratory analysis, descriptive metrics, visualization, and model‑centric inference—provides a framework for understanding and predicting phenomena, emphasizing the role of programming (e.g., Python) and Bayesian modeling principles such as simplicity and the Occam razor.

Modelingdata scienceexploratory data analysis
0 likes · 6 min read
Mastering Model‑Centric Statistics: From Exploratory Analysis to Bayesian Inference
MaGe Linux Operations
MaGe Linux Operations
Sep 24, 2022 · Fundamentals

Boost Your Jupyter Notebook Productivity with 5 Essential Extensions

This guide walks you through installing Jupyter Notebook extensions, explains why they improve workflow, and highlights five must‑have add‑ons—including Table of Contents, Autopep8, Variable Inspector, ExecuteTime, and Hide Code—to streamline data‑science tasks.

ExtensionsJupyter Notebookdata science
0 likes · 7 min read
Boost Your Jupyter Notebook Productivity with 5 Essential Extensions
21CTO
21CTO
Sep 22, 2022 · Fundamentals

Why Every Developer Needs to Master Software Frameworks (And How to Get Started)

This article explains what software frameworks are, why they are essential for developers, outlines the main types—including frontend, backend, mobile, and data‑science frameworks—and offers practical advice on how beginners can start learning them effectively.

Frontenddata sciencedevelopment
0 likes · 12 min read
Why Every Developer Needs to Master Software Frameworks (And How to Get Started)
Model Perspective
Model Perspective
Sep 18, 2022 · Fundamentals

How to Open and Use Jupyter Notebook Files

This guide explains how to launch Jupyter Notebook, open existing notebook files, and begin working with them, providing clear step‑by‑step instructions for users new to the interactive computing environment, including tips on navigating the interface and saving your work.

Jupyter NotebookPythonTutorial
0 likes · 1 min read
How to Open and Use Jupyter Notebook Files
Huawei Cloud Developer Alliance
Huawei Cloud Developer Alliance
Sep 6, 2022 · Big Data

How China’s Universities Are Redesigning Big Data Education: Insights from the 2nd Virtual Research Meeting

The second virtual research meeting of China’s Data Science Curriculum Group gathered nearly a hundred educators and industry partners in Beijing to discuss new models for big‑data course design, curriculum construction, industry‑academia collaboration, and digital teaching platforms across multiple universities.

Big DataCurriculum DesignIndustry-Academia Collaboration
0 likes · 5 min read
How China’s Universities Are Redesigning Big Data Education: Insights from the 2nd Virtual Research Meeting
Python Programming Learning Circle
Python Programming Learning Circle
Sep 5, 2022 · Artificial Intelligence

Ten Essential Python Libraries for AI, Data Processing, and Model Deployment

This article introduces ten powerful Python libraries—including Awkward Array, Jupytext, Gradio, Hub, AugLy, Evidently, YOLOX, LightSeq, Greykite, and Jina/Finetuner—highlighting their key features, performance benefits, and where to find them, offering developers essential tools for data handling, model deployment, and AI research.

AIOpen SourcePython
0 likes · 8 min read
Ten Essential Python Libraries for AI, Data Processing, and Model Deployment
Model Perspective
Model Perspective
Sep 1, 2022 · Fundamentals

Master Factor Analysis in Python: From Theory to Practical Implementation

This article explains the origins and core concepts of factor analysis, outlines its algorithmic steps, demonstrates how to perform the analysis using Python's factor_analyzer library—including data preparation, adequacy tests, eigenvalue selection, rotation, and visualization—culminating in extracting new latent variables.

Pythondata sciencedimensionality reduction
0 likes · 10 min read
Master Factor Analysis in Python: From Theory to Practical Implementation
Huawei Cloud Developer Alliance
Huawei Cloud Developer Alliance
Aug 25, 2022 · Artificial Intelligence

How the “Yujian Cup” AI Competition is Shaping the Future of Medical Testing in China

The inaugural "Yujian Cup" Medical Testing AI Developer Competition, co‑hosted by Jinyu Medical and Huawei Cloud, gathered 405 international teams, showcased cutting‑edge AI algorithms on real pathology data, awarded a 100,000 CNY prize to the winning team, and outlined plans for future annual events to accelerate AI‑driven healthcare innovation.

AICompetitionHealthcare Innovation
0 likes · 8 min read
How the “Yujian Cup” AI Competition is Shaping the Future of Medical Testing in China
Baidu Geek Talk
Baidu Geek Talk
Aug 15, 2022 · Artificial Intelligence

GEEK TALK: Practical Applications of Augmented Analysis

The article explains Augmented Analysis—using AI‑driven natural‑language queries, intelligent assistants, and automated business insights—to enable non‑technical users to explore data, gain actionable recommendations, and boost business value, illustrated with real‑world use cases and practical guidance for embedding the technology into everyday workflows.

AI in AnalyticsAugmented AnalysisBusiness Intelligence
0 likes · 9 min read
GEEK TALK: Practical Applications of Augmented Analysis
Huawei Cloud Developer Alliance
Huawei Cloud Developer Alliance
Aug 9, 2022 · Big Data

How China’s New Data Science Virtual Lab Is Shaping Future Talent

The Ministry of Education launched the national "Data Science Curriculum Group" virtual teaching and research office in Yinchuan, gathering over 70 universities, publishers and industry partners to discuss curriculum construction, talent training plans, core courses, high‑quality textbooks, Huawei Cloud support, and the development of domestic database systems for higher education.

Big Data EducationCurriculum DevelopmentIndustry-Academia Collaboration
0 likes · 9 min read
How China’s New Data Science Virtual Lab Is Shaping Future Talent
Baobao Algorithm Notes
Baobao Algorithm Notes
Aug 3, 2022 · Industry Insights

How to Package Your Model for Competition Success: The Three‑Step ‘Ancient Kung Fu’ Method

This article outlines a systematic three‑step framework—visual appeal, standout optimization, and comprehensive experiments—to help data‑science teams package and present their models effectively in competitions, complete with practical tips, visual examples, and a GitHub resource for creating compelling model graphics.

competition strategydata sciencemachine learning workflow
0 likes · 7 min read
How to Package Your Model for Competition Success: The Three‑Step ‘Ancient Kung Fu’ Method
Python Programming Learning Circle
Python Programming Learning Circle
Jul 26, 2022 · Fundamentals

Top 10 JupyterLab Extensions to Boost Data‑Science Productivity

This article introduces ten essential JupyterLab extensions—ranging from a debugger and table of contents to spreadsheet integration, system monitoring, AI‑powered code completion, variable inspection, and interactive plotting—that together transform the JupyterLab environment into a more powerful, IDE‑like workspace for Python data‑science developers.

JupyterLabPythondata science
0 likes · 7 min read
Top 10 JupyterLab Extensions to Boost Data‑Science Productivity
MaGe Linux Operations
MaGe Linux Operations
Jul 18, 2022 · Fundamentals

Unlock NumPy: Comprehensive Guide to Array Iteration, Reshaping, and Advanced Operations

Explore a thorough NumPy tutorial covering array iteration with nditer, reshaping functions like reshape, flat, and flatten, dimension modifications, transposition, axis swapping, broadcasting, stacking, concatenation, splitting, element manipulation, string utilities, arithmetic, statistical, sorting, searching, and file I/O, all illustrated with clear Python code examples.

NumPyPythonarray manipulation
0 likes · 26 min read
Unlock NumPy: Comprehensive Guide to Array Iteration, Reshaping, and Advanced Operations
Model Perspective
Model Perspective
Jun 29, 2022 · Fundamentals

Explore 26 Matplotlib Styles and How to Set Chinese Fonts

This guide demonstrates how to list and apply the 26 built‑in Matplotlib plotting styles, visualizes each style in a grid, and shows how to configure Chinese fonts to correctly display non‑ASCII characters in your figures.

Chinese fontsMatplotlibPython visualization
0 likes · 5 min read
Explore 26 Matplotlib Styles and How to Set Chinese Fonts
Meituan Technology Team
Meituan Technology Team
May 26, 2022 · Artificial Intelligence

Academic Salon: Urban Fractal Phenomena and Multi‑Agent Modeling – Lecture by Prof. Li Yong

In a June 1 online salon hosted by the Tsinghua‑Meituan Digital Life Joint Research Institute, Prof. Li Yong presented a novel multi‑agent urban mobility model that links individual movement and social interaction to reproduce city‑scale fractal laws such as Zipf’s distribution, super‑linear scaling, and negative‑exponential population patterns, illustrating a new bridge between micro‑level behavior and macro‑level urban evolution.

Academic SalonArtificial IntelligenceFractal Theory
0 likes · 5 min read
Academic Salon: Urban Fractal Phenomena and Multi‑Agent Modeling – Lecture by Prof. Li Yong
21CTO
21CTO
May 11, 2022 · Artificial Intelligence

How SAS Now Fully Supports Python for Data Science and AI

SAS announced native Python support in its analytics platform, offering code examples, cloud‑native AI capabilities, and seamless integration with SAS Studio and other SAS products to empower data scientists to develop and deploy Python models alongside SAS code.

AICloud NativePROC FCMP
0 likes · 5 min read
How SAS Now Fully Supports Python for Data Science and AI
DataFunTalk
DataFunTalk
May 10, 2022 · Artificial Intelligence

Experimental Science and Causal Inference Forum – Sessions Overview at DataFun Summit 2022

The DataFun Summit 2022 features an Experimental Science and Causal Inference forum where leading data scientists from Didi, Tencent, Google, ByteDance, and others present deep technical talks on causal inference methods, A/B testing, game operations, and advertising experiments, offering practical insights and audience takeaways.

A/B testingAdvertisingdata science
0 likes · 10 min read
Experimental Science and Causal Inference Forum – Sessions Overview at DataFun Summit 2022
DataFunSummit
DataFunSummit
May 5, 2022 · Artificial Intelligence

Advertising Targeting: Pain Points, Audience Insight System, Relationship Network Applications, and Modeling Strategies

The article examines the challenges advertisers face in a monopolized traffic environment, presents a three‑layer audience insight system, explores graph‑based relationship network methods, and discusses various modeling approaches—including single‑stage, cross‑stage, and multi‑task learning—along with practical considerations for data security and platform integration.

AIModelingaudience insight
0 likes · 11 min read
Advertising Targeting: Pain Points, Audience Insight System, Relationship Network Applications, and Modeling Strategies
NetEase Yanxuan Technology Product Team
NetEase Yanxuan Technology Product Team
May 5, 2022 · Artificial Intelligence

Time Series Forecasting Algorithm System in E-commerce: Practice and Applications at NetEase Yanxuan

NetEase Yanxuan built an end‑to‑end time‑series forecasting system for e‑commerce that integrates rich user, product, business and external features with a suite of statistical, machine‑learning and deep‑learning models, delivers predictions via a Tornado‑based service for thousands of SKUs, warehouses, advertising and app traffic, and shows that simpler models like XGBoost often outperform complex deep nets while interpretability and external shocks remain key challenges.

Sales PredictionTime Series ForecastingXGBoost
0 likes · 10 min read
Time Series Forecasting Algorithm System in E-commerce: Practice and Applications at NetEase Yanxuan
Architects Research Society
Architects Research Society
Apr 25, 2022 · Artificial Intelligence

Reflecting on a Decade of Data Science and Implications for Future Visualization Tools

The article reviews a decade‑long growth of data science, defines its multidisciplinary nature, outlines the four high‑level and fourteen low‑level processes, describes nine distinct data‑science roles, and discusses how these insights can guide the design of next‑generation data‑visualization and analysis tools.

Big Datadata scienceroles
0 likes · 10 min read
Reflecting on a Decade of Data Science and Implications for Future Visualization Tools
IT Services Circle
IT Services Circle
Mar 21, 2022 · Fundamentals

Microsoft Open-Source Beginner Courses: Web Development, Machine Learning, IoT, and Data Science

Microsoft offers four open‑source, 12‑week beginner courses on GitHub—Web Development, Machine Learning, Internet of Things, and Data Science—each with over 20 lessons, hands‑on projects, quizzes, assignments, and publicly available repositories, providing a comprehensive entry point for aspiring developers and data professionals.

Beginner CoursesIoTMicrosoft
0 likes · 3 min read
Microsoft Open-Source Beginner Courses: Web Development, Machine Learning, IoT, and Data Science
Python Programming Learning Circle
Python Programming Learning Circle
Mar 18, 2022 · Fundamentals

100 Essential NumPy Operations and Code Snippets

This article presents a comprehensive collection of 100 common NumPy tasks, each accompanied by concise explanations and ready‑to‑run Python code examples that demonstrate array creation, manipulation, mathematical operations, indexing, broadcasting, and advanced techniques for scientific computing.

Tutorialarray-manipulationdata science
0 likes · 25 min read
100 Essential NumPy Operations and Code Snippets
Alimama Tech
Alimama Tech
Jan 5, 2022 · Artificial Intelligence

2021 Review of Alibaba Mama Technology: Advertising Algorithms, AI Research, Open‑Source Projects and Conference Papers

The 2021 Alibaba Mama Technology review, covering its May launch and 237‑day output of 50 technical articles on advertising algorithms, system engineering, intelligent creativity, risk control, plus two open‑source projects and numerous SIGIR, KDD, CIKM and CVPR papers, highlights data‑science, marketing series and engineer‑growth stories.

Algorithm EngineeringArtificial IntelligenceOpen Source
0 likes · 5 min read
2021 Review of Alibaba Mama Technology: Advertising Algorithms, AI Research, Open‑Source Projects and Conference Papers
DataFunSummit
DataFunSummit
Dec 9, 2021 · Big Data

Diagnostic Analytics in Meituan Food Delivery: Methods and Case Studies

This talk by Meituan data analyst Wang Qing explains why diagnostic analytics is essential, outlines its methodology using logical trees and hypothesis-driven approaches, and presents two case studies—weather index modeling and an intelligent anomaly detection system—to illustrate how data-driven diagnosis can pinpoint root causes and improve decision‑making in online food delivery.

Root Cause Analysisanomaly detectiondata science
0 likes · 19 min read
Diagnostic Analytics in Meituan Food Delivery: Methods and Case Studies
DataFunTalk
DataFunTalk
Nov 19, 2021 · Artificial Intelligence

Industrial Intelligence: Current Status, Talent, Challenges, and AI Application in Manufacturing

This article examines industrial intelligence from the perspectives of flow and fusion, detailing its current state, talent needs, pain points, AI development processes, edge‑cloud architecture, and key characteristics such as timeliness, reliability, explainability, and applicability in manufacturing.

AI workflowEdge computingdata science
0 likes · 22 min read
Industrial Intelligence: Current Status, Talent, Challenges, and AI Application in Manufacturing
Python Crawling & Data Mining
Python Crawling & Data Mining
Nov 11, 2021 · Fundamentals

Master Jupyter Notebook: Tips, Extensions, and Pro Shortcuts

This comprehensive guide walks you through Jupyter Notebook’s web‑based interactive computing features, major users, installation via Anaconda, launching, dual command/edit modes, core functionalities, useful extensions, keyboard shortcuts, magic commands, and theme customization, providing practical code snippets and visual examples for Python developers.

AnacondaExtensionsInteractive Computing
0 likes · 13 min read
Master Jupyter Notebook: Tips, Extensions, and Pro Shortcuts
Alimama Tech
Alimama Tech
Nov 10, 2021 · Industry Insights

Rethinking Traditional Marketing Models: A Pragmatic C.M.O. Framework

This article distills complex marketing analysis into a concise, data‑driven framework by revisiting classic models, introducing simplified 4P/4C/4R concepts, and presenting the C.M.O. (Customer Insight, Multi‑Touch Attribution, Opportunity) methodology for actionable, high‑dimensional insight generation.

AnalysisCMOIndustry Insights
0 likes · 11 min read
Rethinking Traditional Marketing Models: A Pragmatic C.M.O. Framework
DataFunSummit
DataFunSummit
Nov 5, 2021 · Artificial Intelligence

Practical Insights into Online Experiment Design and Analysis at Tencent Lookpoint

The presentation offers a comprehensive overview of online experiment fundamentals, design variations, and real-world case studies from Tencent Lookpoint, emphasizing hypothesis validation, causal analysis, best practices, and actionable recommendations for improving product growth and decision‑making.

A/B testingRecommendation Systemscausal inference
0 likes · 20 min read
Practical Insights into Online Experiment Design and Analysis at Tencent Lookpoint
DataFunTalk
DataFunTalk
Nov 4, 2021 · Artificial Intelligence

Diagnostic Analytics: Methods, Case Studies, and Common Pitfalls in Business Data Analysis

This article explains why diagnostic analytics is essential, defines the concept, outlines problem types, presents a logical‑tree and hypothesis‑driven methodology, showcases two real‑world projects (weather‑impact index and an intelligent anomaly‑diagnosis system), and highlights frequent mistakes to avoid.

AI modelingBusiness IntelligenceCase study
0 likes · 15 min read
Diagnostic Analytics: Methods, Case Studies, and Common Pitfalls in Business Data Analysis
Alimama Tech
Alimama Tech
Oct 20, 2021 · Big Data

Designing Evaluation Metrics and Building an Overall Evaluation Index (OEC) for AB Testing

The article explains how to design experiment evaluation metrics—from top‑down objectives to core, quality, and observation types—and construct an Overall Evaluation Criterion by processing, weighting, and aggregating metrics, providing a robust, scalable framework for credible AB‑test assessment and product optimization.

AB testingExperiment EvaluationMetric Design
0 likes · 11 min read
Designing Evaluation Metrics and Building an Overall Evaluation Index (OEC) for AB Testing
Alimama Tech
Alimama Tech
Oct 13, 2021 · Artificial Intelligence

Bootstrap Methods for Statistical Inference in AB Testing

The article explains how the non‑parametric Bootstrap resampling method provides a practical, computationally efficient way to perform statistical inference in AB testing—especially with small samples, skewed data, or ratio metrics—by generating confidence intervals and hypothesis tests via repeated sampling, outperforming traditional approaches.

AB testingBootstrapconfidence interval
0 likes · 9 min read
Bootstrap Methods for Statistical Inference in AB Testing
IT Architects Alliance
IT Architects Alliance
Oct 1, 2021 · Fundamentals

Curated List of Must‑Read Technical Books for Various Software Development Domains

This article presents a comprehensive, categorized collection of essential technical books covering frontend development, backend engineering, mobile app creation, server architecture, testing practices, multimedia processing, computer vision, data mining, recommendation systems, and 3D/AR technologies, offering readers valuable resources for deepening their expertise across the software development spectrum.

BooksFrontendLearning Resources
0 likes · 9 min read
Curated List of Must‑Read Technical Books for Various Software Development Domains
Architects Research Society
Architects Research Society
Sep 4, 2021 · Databases

Why Data Scientists Should Learn PostgreSQL

This article explains why mastering SQL and PostgreSQL is essential for data scientists, outlines the core skills of the role, describes PostgreSQL’s features, lists its advantages and drawbacks for data science, and suggests resources for getting started.

Big DataHTAPPostgreSQL
0 likes · 10 min read
Why Data Scientists Should Learn PostgreSQL
21CTO
21CTO
Aug 6, 2021 · Big Data

What the 2021 State of Data Science Reveals About Python, Automation, and Open Source

The 2021 State of Data Science report shows how COVID‑19 has impacted investment, highlights Python's dominance, examines automation's growing role, and reveals corporate attitudes toward open‑source contributions, offering data‑driven insights for professionals and educators alike.

AutomationBig DataOpen Source
0 likes · 5 min read
What the 2021 State of Data Science Reveals About Python, Automation, and Open Source
Programmer DD
Programmer DD
Aug 5, 2021 · Fundamentals

Why Julia Is the High-Paying Language You Should Learn in 2021

Julia, the high‑performance language created at MIT, has secured $24 million in Series A funding, is used by thousands of top companies, offers some of the highest developer salaries, and now has a curated list of free courses and books for beginners.

JuliaLearning Resourcesdata science
0 likes · 4 min read
Why Julia Is the High-Paying Language You Should Learn in 2021
Python Programming Learning Circle
Python Programming Learning Circle
Aug 3, 2021 · Fundamentals

Practical Python Data Cleaning Functions

This article presents a collection of straightforward yet practical Python functions for data cleaning tasks—including dropping columns, changing data types, converting categorical variables, handling missing values, removing unwanted characters, trimming whitespace, conditional concatenation, and converting string timestamps—designed to streamline preprocessing in data analysis projects.

data preprocessingdata science
0 likes · 7 min read
Practical Python Data Cleaning Functions
Python Programming Learning Circle
Python Programming Learning Circle
Jul 29, 2021 · Fundamentals

Understanding NumPy Arrays: Basics, Creation, and Indexing

NumPy arrays are homogeneous, memory‑efficient data structures that outperform Python lists, offering fast creation, shape and rank metadata, and indexed access; this article explains why to use NumPy, defines arrays, and demonstrates array creation and element retrieval with example code.

ArraysNumPyProgramming Fundamentals
0 likes · 3 min read
Understanding NumPy Arrays: Basics, Creation, and Indexing
Python Crawling & Data Mining
Python Crawling & Data Mining
Jul 24, 2021 · Fundamentals

Master Pandas: A Step‑by‑Step Guide to Data Analysis with Python

This comprehensive tutorial introduces Pandas—the powerful Python library for data manipulation and analysis—covers installation, data import, inspection, cleaning, indexing, selection, sorting, grouping, transformation, statistical functions, visualization, and exporting, all illustrated with clear code examples and visual outputs.

Data AnalysisJupyter NotebookPandas
0 likes · 18 min read
Master Pandas: A Step‑by‑Step Guide to Data Analysis with Python
Python Programming Learning Circle
Python Programming Learning Circle
Jun 15, 2021 · Fundamentals

Top 8 Python Tools for Programmers and Students

This article introduces eight widely used Python tools—including IDLE, Scikit-learn, Theano, Selenium, TestComplete, Beautiful Soup, Pandas, and PuLP—detailing their primary features, typical use cases in data science, web automation, and optimization, and offering guidance for programmers and students seeking to enhance their workflow.

data sciencetools
0 likes · 5 min read
Top 8 Python Tools for Programmers and Students
Python Programming Learning Circle
Python Programming Learning Circle
May 24, 2021 · Artificial Intelligence

Useful Python Libraries for Data Science Beyond Pandas and NumPy

This article introduces a curated selection of lesser‑known Python libraries for data‑science tasks—including data acquisition, date‑time handling, imbalanced‑learning, fast keyword extraction, fuzzy string matching, time‑series modeling, 3‑D visualization, web‑app building, and reinforcement‑learning—providing installation commands and concise usage examples.

LibrariesNLPdata science
0 likes · 10 min read
Useful Python Libraries for Data Science Beyond Pandas and NumPy
MaGe Linux Operations
MaGe Linux Operations
Apr 23, 2021 · Artificial Intelligence

Why Python Dominates Machine Learning and AI Development

Python has become the go‑to language for AI and machine learning across startups and enterprises because of its rapid prototyping, flexible syntax, readability, extensive libraries like NumPy, SciPy, scikit‑learn, Pandas, Keras, and powerful visualization tools, making development faster, scalable, and easier to maintain.

Artificial IntelligencePythondata science
0 likes · 8 min read
Why Python Dominates Machine Learning and AI Development
Python Programming Learning Circle
Python Programming Learning Circle
Feb 4, 2021 · Fundamentals

11 Best Python Compilers and Interpreters for Developers

This article introduces Python as a beginner‑friendly, multi‑purpose language and presents eleven notable Python compilers and interpreters—including Brython, Pyjs, WinPython, Skulpt, Shed Skin, ActivePython, Transcrypt, Nutika, Jython, CPython, and IronPython—highlighting their main features, platforms, and typical use cases.

Compilerdata sciencelanguage
0 likes · 8 min read
11 Best Python Compilers and Interpreters for Developers
MaGe Linux Operations
MaGe Linux Operations
Jan 28, 2021 · Fundamentals

Unlock the Power of NumPy: Visual Guide to Arrays and Operations

This article provides a visual, step‑by‑step introduction to NumPy’s core concepts—vectors, matrices, higher‑dimensional arrays, creation, indexing, arithmetic, broadcasting, and common functions—helping developers and researchers understand how the library works and apply it efficiently in Python data‑science workflows.

Array OperationsNumPyPython
0 likes · 18 min read
Unlock the Power of NumPy: Visual Guide to Arrays and Operations
MaGe Linux Operations
MaGe Linux Operations
Jan 17, 2021 · Artificial Intelligence

Top 10 Must‑Know Python Libraries of 2020 (Plus Bonus Picks)

This article presents the 2020 Python library ranking, explaining the selection criteria and highlighting ten standout libraries—ranging from CLI tools like Typer and Rich to AI‑focused frameworks such as Hydra, PyTorch Lightning, Hummingbird, and HiPlot—plus several honorable mentions.

AICLILibraries
0 likes · 13 min read
Top 10 Must‑Know Python Libraries of 2020 (Plus Bonus Picks)
Programmer DD
Programmer DD
Jan 14, 2021 · Artificial Intelligence

What Are Alibaba DAMO Academy’s 2021 Top Ten Tech Trends Shaping the Future?

Alibaba’s DAMO Academy unveils its 2021 top ten technology trends, highlighting breakthroughs in third‑generation semiconductors, post‑quantum computing, flexible carbon‑based electronics, AI‑driven drug discovery, brain‑computer interfaces, autonomous data processing, cloud‑native architectures, smart agriculture, industrial IoT, and intelligent city operation centers.

AISmart Citiesdata science
0 likes · 7 min read
What Are Alibaba DAMO Academy’s 2021 Top Ten Tech Trends Shaping the Future?
Python Programming Learning Circle
Python Programming Learning Circle
Dec 16, 2020 · Artificial Intelligence

Linear Regression Theory and Python Implementation with Iris and Boston Datasets

This article explains the fundamentals of linear regression, including regression formulas, loss functions, and error metrics, and provides complete Python code using scikit‑learn to perform both simple and multiple linear regression on the Iris and Boston housing datasets, along with model evaluation and visualization.

Linear RegressionPythondata science
0 likes · 7 min read
Linear Regression Theory and Python Implementation with Iris and Boston Datasets
21CTO
21CTO
Nov 29, 2020 · Artificial Intelligence

Decode Math Symbols with Python: From Summation to Matrix Multiplication

Learn how to translate common mathematical symbols such as summation, product, factorial, conditional expressions, and matrix multiplication into clear Python code, revealing the underlying computations and helping data scientists and ML practitioners deepen their mathematical intuition through practical examples.

MathematicsMatrix multiplicationPython
0 likes · 7 min read
Decode Math Symbols with Python: From Summation to Matrix Multiplication
Tencent Advertising Technology
Tencent Advertising Technology
Oct 29, 2020 · Artificial Intelligence

Large-Scale User Visits Understanding and Forecasting with Deep Spatial-Temporal Tensor Factorization Framework

This article discusses a deep spatial-temporal tensor factorization framework for large-scale user visits understanding and forecasting, addressing challenges in advertising inventory prediction and demonstrating significant improvements over traditional methods.

Artificial IntelligenceTime Series Forecastingadvertising inventory prediction
0 likes · 9 min read
Large-Scale User Visits Understanding and Forecasting with Deep Spatial-Temporal Tensor Factorization Framework
FunTester
FunTester
Oct 14, 2020 · Operations

Beyond Functional Testing: How Test Engineers Can Add Value Through QAOps, Automation, Stakeholder Collaboration, and Data Science

The article explains how test engineers can extend their impact beyond functional testing by engaging stakeholders, adopting QAOps practices, listening to user feedback, exploring automation tools, participating in code reviews, focusing on user experience, meeting deadlines, and leveraging data science to improve software quality.

AutomationCI/CDQAOps
0 likes · 13 min read
Beyond Functional Testing: How Test Engineers Can Add Value Through QAOps, Automation, Stakeholder Collaboration, and Data Science
DataFunTalk
DataFunTalk
Sep 26, 2020 · Artificial Intelligence

What Makes a Good Model? Understanding Model Concepts, Types, and Evaluation in Data Science

This article explores the definition of a model, distinguishes business, data, and function models, discusses criteria for a good model—including performance, fidelity to real‑world relationships, and interpretability—and examines why a universal model does not exist, all within the context of data science and AI.

AIModelModel Evaluation
0 likes · 18 min read
What Makes a Good Model? Understanding Model Concepts, Types, and Evaluation in Data Science
Beike Product & Technology
Beike Product & Technology
Sep 17, 2020 · Artificial Intelligence

User Preference Mining in Real Estate: Techniques and Applications

This paper explores user preference mining techniques in real estate, utilizing statistical methods and machine learning models like XGBoost, LSTM, and Seq4Rec to address challenges in high-dimensional, sparse data, enhancing personalized recommendations and marketing strategies.

data sciencereal estateuser preference mining
0 likes · 15 min read
User Preference Mining in Real Estate: Techniques and Applications
Architects Research Society
Architects Research Society
Aug 29, 2020 · Databases

Why Data Scientists Should Learn PostgreSQL

The article explains why SQL is essential for data scientists, introduces PostgreSQL as a powerful open‑source relational database suited for large‑scale data science, outlines its key features, advantages and disadvantages, and provides practical learning resources for beginners.

DatabaseLearning ResourcesPostgreSQL
0 likes · 9 min read
Why Data Scientists Should Learn PostgreSQL
Python Crawling & Data Mining
Python Crawling & Data Mining
Aug 28, 2020 · Artificial Intelligence

Build and Optimize Multiple Linear Regression in Python

This article walks through constructing a multiple linear regression model for house price prediction using Python, covering data exploration, dummy variable creation, model fitting with statsmodels, diagnosing multicollinearity via VIF, and applying optimizations to improve predictive accuracy.

Dummy VariablesMultiple Linear RegressionPython
0 likes · 11 min read
Build and Optimize Multiple Linear Regression in Python
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 25, 2020 · Artificial Intelligence

Build a Free Cloud AI Speed‑Dating Model with Alibaba PAI‑DSW

This article introduces Alibaba Cloud’s free PAI‑DSW cloud IDE for AI development, explains the evolution of machine learning, guides users through creating notebooks, running Python code, and demonstrates a complete speed‑dating dataset analysis and predictive modeling pipeline using logistic regression and data‑balancing techniques.

AICloud IDEPython
0 likes · 21 min read
Build a Free Cloud AI Speed‑Dating Model with Alibaba PAI‑DSW
MaGe Linux Operations
MaGe Linux Operations
Aug 20, 2020 · Artificial Intelligence

Explore 10 Lesser-Known Python Libraries for Data Science & AI

This article introduces a curated selection of lesser‑known Python packages—such as wget, pendulum, imbalanced‑learn, FlashText, fuzzywuzzy, PyFlux, ipyvolume, Dash, and Gym—detailing their installation commands, core functionalities, and code examples to help data scientists expand their toolkit beyond the usual pandas, scikit‑learn, and matplotlib.

LibrariesNLPPython
0 likes · 9 min read
Explore 10 Lesser-Known Python Libraries for Data Science & AI
MaGe Linux Operations
MaGe Linux Operations
Jul 28, 2020 · Fundamentals

Top 8 Python Tools Every Programmer and Student Should Know

This article reviews eight essential Python tools—including IDLE, Scikit‑learn, Theano, Selenium, TestComplete, BeautifulSoup, Pandas, and PuLP—explaining their main features, typical use cases, and why they are valuable for developers and students across web, data science, automation, and optimization tasks.

PythonWeb Scrapingdata science
0 likes · 5 min read
Top 8 Python Tools Every Programmer and Student Should Know
AntTech
AntTech
Jul 16, 2020 · Artificial Intelligence

Why Go+ Can Complement Python for Data‑Science and Deep‑Learning Workflows

The article argues that Go+, by preserving Go's concise syntax while adding Python‑like type inference and tensor support, can address Python's flexibility‑induced code‑quality and performance issues, making it a viable front‑end language for data‑science, deep‑learning libraries, and compiler ecosystems.

CompilerGo+Programming Language
0 likes · 15 min read
Why Go+ Can Complement Python for Data‑Science and Deep‑Learning Workflows
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 16, 2020 · Artificial Intelligence

Can Go+ Fill Python’s Gaps in Data Science and Deep Learning?

After years of using Python for AI and data science, the author examines its flexibility drawbacks and argues that Go+, with its static typing and concise syntax, can address Python’s limitations, offering comparable ease for tensor operations, potential for a new deep‑learning front‑end language.

CompilerGoProgramming Languages
0 likes · 16 min read
Can Go+ Fill Python’s Gaps in Data Science and Deep Learning?
Architects Research Society
Architects Research Society
Jul 10, 2020 · Artificial Intelligence

Core Concepts and Relationships in Data Science: Big Data, Machine Learning, Data Mining, Deep Learning, and AI

This article examines six core data‑science concepts—Big Data, Machine Learning, Data Mining, Deep Learning, Artificial Intelligence, and Data Science itself—explaining their definitions, interrelationships, and how they fit together as pieces of a larger analytical puzzle.

Artificial Intelligencedata miningdata science
0 likes · 17 min read
Core Concepts and Relationships in Data Science: Big Data, Machine Learning, Data Mining, Deep Learning, and AI
Python Programming Learning Circle
Python Programming Learning Circle
Jun 17, 2020 · Fundamentals

53 Python Interview Questions and Answers

This article compiles 53 common Python interview questions covering fundamentals, data structures, functions, OOP, and standard library features, providing concise explanations and code examples to help data scientists and developers prepare for technical interviews.

Interviewanswersdata science
0 likes · 21 min read
53 Python Interview Questions and Answers
Laravel Tech Community
Laravel Tech Community
May 22, 2020 · Fundamentals

2020 Developer Internet Survey Highlights Go Popularity, Data Science Interest, and Remote Work Preferences

The 2020 developer internet survey reveals that Go tops the list of languages developers want to learn, data science dominates interest areas, security and IoT follow, and remote/online work and learning are increasingly preferred, while experienced developers show limited expertise in machine learning.

Developer SurveyGo languageProgramming Languages
0 likes · 3 min read
2020 Developer Internet Survey Highlights Go Popularity, Data Science Interest, and Remote Work Preferences
21CTO
21CTO
Apr 3, 2020 · Artificial Intelligence

How Engineers Became the New Rulers: The Rise of Algorithms and Their Societal Impact

This essay traces the historical shift from political power to engineering dominance, exploring how algorithms—originating from thinkers like Leibniz and popularized by tech giants such as Facebook—have reshaped governance, culture, and the very fabric of human decision‑making.

Algorithmsdata sciencesocial media
0 likes · 24 min read
How Engineers Became the New Rulers: The Rise of Algorithms and Their Societal Impact
Python Programming Learning Circle
Python Programming Learning Circle
Nov 2, 2019 · Artificial Intelligence

Master the 5 Essential Steps of Data Science with Key Python Libraries

This guide walks through the five essential steps of a data‑science project—acquiring, cleaning, exploring, modeling, and presenting data—while highlighting key Python libraries such as Beautiful Soup, Requests, Pandas, NumPy, Seaborn, Matplotlib, and Scikit‑learn, and providing installation and import commands.

Librariesdata science
0 likes · 8 min read
Master the 5 Essential Steps of Data Science with Key Python Libraries
Didi Tech
Didi Tech
Oct 8, 2019 · Artificial Intelligence

Didi and Ant Financial Co‑Develop SQLFlow to Bring AI Capabilities to Data Analysts

Partnering with Ant Financial, Didi enhanced the open-source SQLFlow platform—translating SQL into end-to-end AI workflows with added deep-learning, XGBoost, clustering and SHAP explanation capabilities and Hive support—to create a “SQL garden” marketplace where analysts can deploy ready-made AI models via simple SQL, speeding enterprise AI adoption.

AIOpen SourceSHAP
0 likes · 9 min read
Didi and Ant Financial Co‑Develop SQLFlow to Bring AI Capabilities to Data Analysts
ITPUB
ITPUB
Sep 27, 2019 · Artificial Intelligence

How Didi and Ant Financial Co‑Built SQLFlow to Bring AI to Data Analysts

The article describes how Didi's data science team partnered with Ant Financial to open‑source SQLFlow, a tool that translates SQL into Python for AI model training and inference, enabling analysts to use familiar SQL to run deep‑learning, XGBoost, and clustering models across diverse business scenarios.

AISQLSQLFlow
0 likes · 9 min read
How Didi and Ant Financial Co‑Built SQLFlow to Bring AI to Data Analysts
ITPUB
ITPUB
Sep 25, 2019 · Artificial Intelligence

From Physics to Kaggle Grandmaster: A Data Scientist’s Journey and Advice

Physicist‑turned‑Kaggle Grandmaster Bojan Tunguz shares his journey from academia to industry, the challenges of becoming a data‑science competitor, his workflow, favorite tools, and practical advice for newcomers seeking to excel in machine‑learning competitions.

Artificial IntelligenceKaggledata science
0 likes · 10 min read
From Physics to Kaggle Grandmaster: A Data Scientist’s Journey and Advice
Tencent Cloud Developer
Tencent Cloud Developer
Sep 17, 2019 · Artificial Intelligence

Intelligent Ti Machine Learning Platform: Industrial and Financial Applications

Tencent Cloud’s Intelligent Ti Machine Learning Platform (TI‑ONE) offers a one‑stop, drag‑and‑drop solution for data preprocessing, model training, and deployment across industrial panel defect detection and financial risk prediction, delivering real‑time monitoring, automated pipelines, and high‑accuracy results that dramatically improve operational efficiency.

AIAutomationFinancial AI
0 likes · 16 min read
Intelligent Ti Machine Learning Platform: Industrial and Financial Applications
21CTO
21CTO
Aug 19, 2019 · Fundamentals

Is Python Overtaking R? A Deep Dive into Language Popularity Trends

This article examines how Python has surged to become the leading language for data science, while R's popularity has declined, citing TIOBE rankings, industry surveys, academic adoption, and expert opinions to assess whether R is truly on the brink of obsolescence.

Language PopularityPythonR
0 likes · 8 min read
Is Python Overtaking R? A Deep Dive into Language Popularity Trends
Python Crawling & Data Mining
Python Crawling & Data Mining
Aug 16, 2019 · Fundamentals

Master NumPy: Essential Array and Matrix Operations for Data Science

This guide introduces NumPy's core features—including array creation, arithmetic, indexing, aggregation, multi‑dimensional handling, matrix operations, and practical examples such as computing mean‑square error—providing a comprehensive foundation for Python‑based data analysis and machine‑learning workflows.

Array OperationsMatrix ComputationPython
0 likes · 10 min read
Master NumPy: Essential Array and Matrix Operations for Data Science
Tencent Advertising Technology
Tencent Advertising Technology
May 27, 2019 · Artificial Intelligence

Practical Tips for Efficient and Clean Code in the Tencent Advertising Algorithm Competition

In this presentation, a veteran participant of the Tencent Advertising Algorithm Competition shares practical advice on building simple, efficient models, optimizing code performance, managing version control with Git, and maintaining clean coding practices to improve competition outcomes and foster better engineering habits.

Competitioncode optimizationdata science
0 likes · 7 min read
Practical Tips for Efficient and Clean Code in the Tencent Advertising Algorithm Competition
Didi Tech
Didi Tech
May 9, 2019 · Artificial Intelligence

Weber-Fechner Law, Prospect Theory, and Their Data Science Applications

The article explains the Weber‑Fechner law and its role in Prospect Theory, then shows how Didi applies these concepts—using a log‑linear order‑distance model and reference‑point‑based strategy evaluation—to reduce cancellations, improve driver perception, and guide data‑driven product decisions.

DidiLogistic RegressionPsychophysics
0 likes · 9 min read
Weber-Fechner Law, Prospect Theory, and Their Data Science Applications
HomeTech
HomeTech
Apr 25, 2019 · Artificial Intelligence

An Introduction to Artificial Intelligence: Basics, Applications, and How to Get Started

This article provides a beginner-friendly overview of artificial intelligence, explaining its core concepts, the relationship between AI, machine learning and deep learning, common real-world applications such as search and recommendation, and practical steps and resources for newcomers to start learning AI with Python and basic statistics.

AIPythondata science
0 likes · 8 min read
An Introduction to Artificial Intelligence: Basics, Applications, and How to Get Started
Didi Tech
Didi Tech
Apr 18, 2019 · Industry Insights

What Defines a Data Scientist’s Role and How It Should Evolve?

The article examines the emerging data‑science function, clarifies who data scientists are, outlines their core tasks—describing the current state, uncovering patterns, and driving improvement—while proposing future growth through capability and culture building, and summarising ten guiding principles for effective analysis.

Industry Insightscapability buildingculture development
0 likes · 11 min read
What Defines a Data Scientist’s Role and How It Should Evolve?
DataFunTalk
DataFunTalk
Apr 8, 2019 · Artificial Intelligence

AI Scientific Frontier Conference 2019 – Program, Speakers, and Schedule

The AI Scientific Frontier Conference 2019, co‑hosted by the Chinese Academy of Sciences AI Alliance and Beijing Institute of Technology, gathers leading researchers to present cutting‑edge talks on AI theory, deep learning, computer vision, robotics, NLP, big data, and related applications, with detailed schedules, speaker bios, venue information, and registration details provided.

AINLPdata science
0 likes · 60 min read
AI Scientific Frontier Conference 2019 – Program, Speakers, and Schedule
JD Tech Talk
JD Tech Talk
Mar 1, 2019 · Artificial Intelligence

Introduction to H2O AutoML: Overview, Practical Workflow, and Model Deployment

This article introduces the open‑source H2O platform, explains how to install and use its Python API for data loading, preprocessing, model training with GBM and AutoML, evaluates results with AUC, and describes model deployment via POJO/MOJO as well as the visual Flow UI, concluding with reflections on the role of automated modeling in data science.

AutoMLH2OModel deployment
0 likes · 12 min read
Introduction to H2O AutoML: Overview, Practical Workflow, and Model Deployment
Python Crawling & Data Mining
Python Crawling & Data Mining
Feb 27, 2019 · Fundamentals

R vs Python for Data Analysis: Which Language Wins?

This article presents a detailed infographic comparison of R and Python from a data‑science perspective, outlining their histories, ecosystems, usability, community support, and advantages in data analysis to help readers decide which language better fits their projects.

ComparisonData AnalysisPython
0 likes · 5 min read
R vs Python for Data Analysis: Which Language Wins?
MaGe Linux Operations
MaGe Linux Operations
Feb 4, 2019 · Artificial Intelligence

8 Python Linear Regression Techniques Compared for Speed and Complexity

This article reviews eight Python-based simple linear regression algorithms, examining their computational complexity and speed on datasets up to ten million points, highlighting trade‑offs between ease of use, flexibility, and performance to help data scientists choose the most efficient method.

Linear RegressionPythondata science
0 likes · 10 min read
8 Python Linear Regression Techniques Compared for Speed and Complexity
21CTO
21CTO
Dec 10, 2018 · Fundamentals

10 Compelling Reasons to Learn Python in 2018 (And Why It Beats Java)

This article explains why Python has overtaken Java in popularity, presents PYPL index data, and outlines ten practical reasons—from data science and machine learning to web development and automation—that make learning Python in 2018 a smart career move.

Pythoncareer developmentdata science
0 likes · 11 min read
10 Compelling Reasons to Learn Python in 2018 (And Why It Beats Java)
MaGe Linux Operations
MaGe Linux Operations
Nov 26, 2018 · Artificial Intelligence

Master Python Machine Learning in 14 Steps: From Zero to Expert

This comprehensive guide walks beginners through fourteen practical steps to learn Python machine learning, covering essential Python skills, core scientific libraries, fundamental algorithms, advanced techniques like SVM and ensemble methods, dimensionality reduction, and deep learning with TensorFlow, all using free online resources.

Pythondata sciencedeep learning
0 likes · 22 min read
Master Python Machine Learning in 14 Steps: From Zero to Expert
ITPUB
ITPUB
Nov 25, 2018 · Artificial Intelligence

Top 10 In-Demand IT Skills for 2019: From DevOps to AI and Cloud

This article outlines the ten most sought‑after technical skills for IT professionals in 2019, covering DevOps, Hadoop, Python/Django, data‑science tools, machine learning, AI, RPA, AWS, Tableau, and digital‑marketing analytics, with market trends and certification guidance.

Artificial IntelligenceCloud ComputingDevOps
0 likes · 10 min read
Top 10 In-Demand IT Skills for 2019: From DevOps to AI and Cloud
ITPUB
ITPUB
Nov 20, 2018 · Fundamentals

Top 10 In‑Demand IT Skills for 2019 Every Engineer Should Master

This article outlines the ten most sought‑after technical competencies for 2019—including DevOps, Hadoop, Python/Django, data‑science tools, machine learning, AI, RPA, AWS, Tableau, and digital‑marketing analytics—explaining why each skill matters, key tools to learn, and the market demand behind them.

Artificial IntelligenceCloud ComputingDevOps
0 likes · 8 min read
Top 10 In‑Demand IT Skills for 2019 Every Engineer Should Master