Jupyter | BestHub

Python Programming Learning Circle

Apr 30, 2025 · Artificial Intelligence

Homemade Machine Learning: Python Implementations of Popular Machine Learning Algorithms with Jupyter Notebook Demos

The article presents the Homemade Machine Learning GitHub repository, which offers from‑scratch Python implementations of popular supervised and unsupervised algorithms, complete with mathematical explanations, code samples, and interactive Jupyter Notebook demonstrations, along with setup instructions and dataset links.

AIAlgorithmsGitHub

0 likes · 6 min read

Homemade Machine Learning: Python Implementations of Popular Machine Learning Algorithms with Jupyter Notebook Demos

Python Programming Learning Circle

Apr 17, 2025 · Artificial Intelligence

Homemade Machine Learning: Python Implementations of Popular Algorithms with Jupyter Demos

This article introduces the GitHub repository “Homemade Machine Learning,” which provides pure‑Python implementations of popular supervised and unsupervised algorithms—including linear and logistic regression, K‑means clustering, anomaly detection, and multilayer perceptrons—accompanied by mathematical explanations, code samples, and interactive Jupyter Notebook demonstrations.

AlgorithmsEducationalJupyter

0 likes · 5 min read

Homemade Machine Learning: Python Implementations of Popular Algorithms with Jupyter Demos

Python Programming Learning Circle

Jan 22, 2025 · Backend Development

JupyterLab Visual Debugger: Installation, Features, and Usage

This article introduces the newly released JupyterLab visual debugger, explains why debugging is needed in Jupyter, provides step‑by‑step installation commands for the frontend extension and xeus‑python kernel, and highlights key UI features and related VS Code visual debugging tools.

DebuggerJupyterPython

0 likes · 7 min read

JupyterLab Visual Debugger: Installation, Features, and Usage

Python Programming Learning Circle

Jul 11, 2024 · Fundamentals

Critical Review of Python in Excel: Limitations, Use Cases, and Recommendations

The article provides a detailed technical analysis of Microsoft’s preview‑only Python in Excel feature, outlining its current capabilities, major limitations such as lack of VBA replacement, restricted package usage, cloud‑dependency, and workflow friction, while suggesting improvements and alternative approaches for data‑centric users.

AzureExcelJupyter

0 likes · 16 min read

Critical Review of Python in Excel: Limitations, Use Cases, and Recommendations

Python Programming Learning Circle

Jun 27, 2024 · Artificial Intelligence

Homemade Machine Learning – Python Implementations of Popular Algorithms with Jupyter Notebooks

This article introduces the GitHub "Homemade Machine Learning" project, which provides pure‑Python implementations of common supervised and unsupervised machine‑learning algorithms, complete with mathematical explanations, Jupyter‑Notebook demos, installation instructions, and links to datasets for hands‑on learning.

AIAlgorithmsJupyter

0 likes · 6 min read

Homemade Machine Learning – Python Implementations of Popular Algorithms with Jupyter Notebooks

Python Programming Learning Circle

Feb 17, 2024 · Fundamentals

Interactive DataFrame Visualization Tools in Python: pivottablejs, PyGWalker, Qgrid, and Itables

This article introduces four Python packages—pivottablejs, PyGWalker, Qgrid, and Itables—that transform Pandas DataFrames into interactive, visual tables within notebooks, providing code examples and screenshots to demonstrate how to create, explore, and edit data interactively.

Interactive TablesJupyterPython

0 likes · 4 min read

Interactive DataFrame Visualization Tools in Python: pivottablejs, PyGWalker, Qgrid, and Itables

Python Programming Learning Circle

Nov 25, 2023 · Fundamentals

Interactive DataFrames in Jupyter: Using Pivottablejs, PyGWalker, Qgrid, and Itables

This article introduces four Python packages—Pivottablejs, PyGWalker, Qgrid, and Itables—that transform Pandas DataFrames into interactive tables within Jupyter notebooks, providing code examples, visual demonstrations, and guidance on when to choose each tool for data analysis and visualization.

Jupyterdata analysisinteractive-table

0 likes · 5 min read

Interactive DataFrames in Jupyter: Using Pivottablejs, PyGWalker, Qgrid, and Itables

Architects Research Society

Oct 30, 2023 · Big Data

Essential Data Science Tools for Elevating Analytics Operations

The article surveys the most important data‑science tools—including Jupyter Notebooks, notebook lab platforms, RStudio, Sweave/Knitr, IDEs, domain‑specific solutions, hardware, and data sources—explaining how they support modern, real‑time analytics and help organizations turn raw data into actionable insights.

Big DataJupyterRStudio

0 likes · 10 min read

Essential Data Science Tools for Elevating Analytics Operations

Python Programming Learning Circle

Jun 12, 2023 · Fundamentals

Mojo: A Python‑Compatible Language with Rust‑Level Performance

The article introduces Mojo, a new programming language positioned as a superset of Python that offers Rust‑like speed and safety through ahead‑of‑time compilation, discusses its early‑stage features, performance claims, online playground, and evaluates its potential to complement or replace Python in data‑science and high‑performance scenarios.

JupyterMojodata science

0 likes · 8 min read

Mojo: A Python‑Compatible Language with Rust‑Level Performance

Python Programming Learning Circle

Feb 15, 2023 · Fundamentals

Methods for Monitoring Python Code Execution Time and Memory Usage

This article introduces four practical techniques for measuring Python code performance, including the built‑in time module, Jupyter’s %%time magic, line_profiler for per‑line timing, and memory_profiler for detailed memory consumption, complete with example code and interpretation of results.

JupyterPerformance Profilingline_profiler

0 likes · 7 min read

Methods for Monitoring Python Code Execution Time and Memory Usage

Sohu Tech Products

Oct 12, 2022 · Big Data

Using GoPUP: A Python Library for Easy Access to Public Data APIs

This article introduces the GoPUP Python library, explains how to install it, demonstrates retrieving Weibo index data with code examples, shows how to visualize the results using Pandas, Jupyter and Matplotlib, and lists the wide range of public data APIs the library supports.

GoPUPJupyterPython

0 likes · 7 min read

Using GoPUP: A Python Library for Easy Access to Public Data APIs

Python Programming Learning Circle

Sep 12, 2022 · Fundamentals

Seven Lesser-Known Jupyter Extensions to Boost Your Productivity

This article introduces seven lesser‑known but highly useful Jupyter Notebook extensions—voila, nbdime, RISE, bokeh, nbgrader, jupytext, and jupyterlab‑git—detailing their features, GitHub popularity, and how they can transform notebooks into interactive web apps, version‑controlled documents, slides, visualizations, grading tools, and more.

Jupyterextensionsnbdime

0 likes · 5 min read

Seven Lesser-Known Jupyter Extensions to Boost Your Productivity

Python Programming Learning Circle

Aug 24, 2022 · Fundamentals

7 Essential Jupyter Notebook Tips for Data Analysis: Profiling, Interactive Visualisation, Magic Commands, Formatting, Shortcuts, Multiple Outputs, and Slide Creation

This article presents seven practical techniques for enhancing daily data‑analysis work in Jupyter notebooks, covering Pandas Profiling, Cufflinks/Plotly visualisation, IPython magic commands, markdown formatting, keyboard shortcuts, displaying multiple outputs simultaneously, and converting notebooks into live presentation slides.

IPythonJupyterPython

0 likes · 10 min read

7 Essential Jupyter Notebook Tips for Data Analysis: Profiling, Interactive Visualisation, Magic Commands, Formatting, Shortcuts, Multiple Outputs, and Slide Creation

Python Programming Learning Circle

May 18, 2022 · Backend Development

Microsoft Splits VS Code Python Extension into Black, isort, and Jupyter Powertoys Extensions

Microsoft has recently divided its VS Code Python extension, releasing three independent extensions—Black for code formatting, isort for import sorting, and Jupyter Powertoys for experimental notebook features—each offering LSP‑based support, version checks, and marketplace installation for Python developers.

BlackJupyterPython

0 likes · 5 min read

Microsoft Splits VS Code Python Extension into Black, isort, and Jupyter Powertoys Extensions

Python Programming Learning Circle

Mar 28, 2022 · Fundamentals

Introduction to Altair: A Declarative Python Library for Data Visualization

This article introduces Altair, a simple yet powerful Python library built on the Vega‑Lite JSON specification, explains its declarative syntax, showcases basic and advanced visualizations with code examples, and highlights its advantages for efficient data analysis and presentation.

ChartingJupyterVega-Lite

0 likes · 7 min read

Introduction to Altair: A Declarative Python Library for Data Visualization

Laravel Tech Community

Jan 13, 2022 · Frontend Development

Getting Started with Kepler.gl in Jupyter Notebook: Installation, Basic Usage, and Export

This guide introduces Uber's open‑source Kepler.gl library for geospatial visualization in Jupyter notebooks, covering installation via pip, a simple map example, adding CSV or DataFrame data, customizing through the UI, retrieving configurations, and exporting the map to an HTML file.

JupyterPythondata visualization

0 likes · 4 min read

Getting Started with Kepler.gl in Jupyter Notebook: Installation, Basic Usage, and Export

Python Programming Learning Circle

Dec 14, 2021 · Fundamentals

Using Plotly in Python to Create Line, Scatter, and Bar Charts

This tutorial introduces Plotly for Python, showing how to install it, configure offline mode in Jupyter, and create line, scatter, and bar charts with complete code examples and explanations of each visualization type.

ChartingJupyterPlotly

0 likes · 6 min read

Using Plotly in Python to Create Line, Scatter, and Bar Charts

Python Programming Learning Circle

Nov 30, 2021 · Fundamentals

Using Kepler.gl in Jupyter Notebook for Geospatial Data Visualization

This tutorial introduces Kepler.gl, an open‑source geospatial visualization library from Uber, showing how to install it in a Jupyter notebook, create maps, load CSV or DataFrame data, customize charts via the GUI, retrieve configurations, and export the interactive map to HTML.

JupyterKepler.glPython

0 likes · 5 min read

Using Kepler.gl in Jupyter Notebook for Geospatial Data Visualization

Big Data Technology Architecture

Nov 28, 2021 · Big Data

EMR Studio: Architecture and Features for Simplifying Big Data Development

EMR Studio is a one‑stop, open‑source‑compatible big data development platform that integrates Zeppelin, Jupyter, Airflow and a custom Cluster Manager to streamline job creation, scheduling, monitoring, and cluster switching, thereby addressing common usability challenges in Spark, Flink, Hive, and Presto workflows.

AirflowApache SparkBig Data

0 likes · 9 min read

EMR Studio: Architecture and Features for Simplifying Big Data Development

Python Programming Learning Circle

Jun 11, 2021 · Fundamentals

Using handcalcs to Convert Python Calculations into LaTeX Formulas

handcalcs is an open‑source Python library that automatically transforms calculation code into LaTeX‑styled formulas, offering Jupyter cell magic and decorator interfaces, customizable display options, and support for symbolic, short, and long representations, while noting limitations with collection types and variable reuse.

JupyterLaTeXPython

0 likes · 5 min read

Using handcalcs to Convert Python Calculations into LaTeX Formulas