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php中文网 Courses
php中文网 Courses
May 15, 2025 · Artificial Intelligence

Why Python Dominates Data Analysis and Machine Learning: Core Tools, Full‑Stack Solutions, and Learning Path

This article explains why Python has become the leading language for data analysis and machine learning, outlines the essential libraries and frameworks, provides practical code examples, describes typical application scenarios, suggests a staged learning roadmap, and forecasts future trends such as AutoML and federated learning.

AutoMLPyTorchPython
0 likes · 6 min read
Why Python Dominates Data Analysis and Machine Learning: Core Tools, Full‑Stack Solutions, and Learning Path
Python Programming Learning Circle
Python Programming Learning Circle
Apr 15, 2025 · Artificial Intelligence

Automatic Math Expression Grading with Python, CNN and Image Processing

This tutorial explains how to generate synthetic digit fonts, build a convolutional neural network to recognize handwritten arithmetic expressions, segment images using projection methods, evaluate the results with Python's eval function, and overlay feedback symbols on the original image, providing a complete end‑to‑end solution.

CNNImageProcessingMachineLearning
0 likes · 27 min read
Automatic Math Expression Grading with Python, CNN and Image Processing
Python Programming Learning Circle
Python Programming Learning Circle
Nov 27, 2024 · Artificial Intelligence

Open‑Source Bird Species Detection with TensorFlow, MobileNet V2 and OpenCV

A hobbyist builds a Python‑based bird‑recognition system using TensorFlow's SSD OpenImages model, a MobileNet V2 classifier from TensorFlow Hub, and OpenCV, shares the open‑source code on GitHub, discusses early results, challenges like accuracy and non‑maximum suppression, and outlines future improvements.

Bird DetectionPythonTensorFlow
0 likes · 8 min read
Open‑Source Bird Species Detection with TensorFlow, MobileNet V2 and OpenCV
JD Retail Technology
JD Retail Technology
Aug 30, 2024 · Artificial Intelligence

GPU Optimization Practices for Training and Inference in JD Advertising Recommendation Systems

The article details JD Advertising's technical challenges and solutions for large‑scale sparse recommendation models, describing GPU‑focused storage, compute and I/O optimizations for both training and low‑latency inference, including distributed pipelines, heterogeneous deployment, batch aggregation, multi‑stream execution, and compiler extensions.

GPU optimizationInferenceRecommendation systems
0 likes · 13 min read
GPU Optimization Practices for Training and Inference in JD Advertising Recommendation Systems
DataFunSummit
DataFunSummit
Aug 8, 2024 · Artificial Intelligence

GPU Throughput and Low‑Latency Optimization Practices in JD Advertising

This article presents JD Advertising's technical practices for improving GPU throughput and reducing latency in large‑scale recommendation scenarios, covering system challenges, storage and compute optimizations for training, low‑latency inference techniques, and compiler extensions to handle massive sparse models.

AIGPU optimizationRecommendation systems
0 likes · 13 min read
GPU Throughput and Low‑Latency Optimization Practices in JD Advertising
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
May 17, 2024 · Artificial Intelligence

Building a Low‑Cost AI Image Classification Platform for Edge Devices

This article describes how to create a cheap AI image‑classification system that trains a TensorFlow model on a desktop, converts it to TFLite, and runs it on Android phones and Raspberry Pi devices, detailing data preparation, training, deployment, and hardware considerations.

AIAndroidEdge Computing
0 likes · 9 min read
Building a Low‑Cost AI Image Classification Platform for Edge Devices
Python Programming Learning Circle
Python Programming Learning Circle
May 11, 2024 · Artificial Intelligence

A Comprehensive Overview of Popular Python Libraries for Artificial Intelligence and Data Science

This article introduces and demonstrates more than twenty widely used Python libraries for artificial intelligence, computer vision, natural language processing, and data analysis, providing concise explanations and runnable code snippets that illustrate each library's core functionality and typical use cases.

Artificial IntelligenceNumPyPyTorch
0 likes · 29 min read
A Comprehensive Overview of Popular Python Libraries for Artificial Intelligence and Data Science
Didi Tech
Didi Tech
Apr 16, 2024 · Artificial Intelligence

Optimizing DSP Deep Model Latency by Externalizing Feature Processing with EzFeaFly

By externalizing feature processing with the EzFeaFly tool and feeding a dense index/value tensor directly to the GPU, the DSP platform decouples feature transformation from model inference, cutting instance usage by ~40%, reducing inference latency 70‑80%, and achieving over 60% end‑to‑end latency improvement while lowering costs.

DSPFeature EngineeringGPU Acceleration
0 likes · 11 min read
Optimizing DSP Deep Model Latency by Externalizing Feature Processing with EzFeaFly
iQIYI Technical Product Team
iQIYI Technical Product Team
Mar 15, 2024 · Artificial Intelligence

Optimizing GPU Inference for CTR Models: Kernel Fusion, Multi‑Stream Execution, and Batch Merging

By fusing sparse‑feature operators, enabling multi‑stream execution, consolidating data copies, and merging inference batches, iQIYI reduced GPU CTR model latency to CPU‑level, boosted throughput over sixfold, and cut operational costs by more than 40%, overcoming launch‑overhead bottlenecks.

GPUKernel FusionTensorFlow
0 likes · 10 min read
Optimizing GPU Inference for CTR Models: Kernel Fusion, Multi‑Stream Execution, and Batch Merging
iQIYI Technical Product Team
iQIYI Technical Product Team
Mar 1, 2024 · Artificial Intelligence

Advertising Data Characteristics and Sparse Large‑Model Practices at iQIYI

iQIYI’s ad ranking system replaces static, hash‑based embeddings with TFRA dynamic embeddings to efficiently handle massive sparse ID features, eliminates collisions and I/O bottlenecks, isolates memory during hot model swaps, enabling billion‑parameter models that boost revenue by 4.3 % while planning adaptive embedding sizes for future improvements.

AI recommendationDynamic EmbeddingLarge-Scale Models
0 likes · 10 min read
Advertising Data Characteristics and Sparse Large‑Model Practices at iQIYI
php中文网 Courses
php中文网 Courses
Oct 30, 2023 · Artificial Intelligence

Implementing AI Features in WeChat Mini Programs Using PHP

This article explains how to integrate artificial intelligence into WeChat Mini Programs by deploying a TensorFlow model on a PHP backend, providing step‑by‑step instructions and sample code for creating an API, handling requests with wx.request, and returning predictions to the client.

AIAPITensorFlow
0 likes · 5 min read
Implementing AI Features in WeChat Mini Programs Using PHP
Ximalaya Technology Team
Ximalaya Technology Team
Oct 9, 2023 · Artificial Intelligence

DeepRec-Based High-Dimensional Sparse Feature Support and Real-Time Model Training in Ximalaya AI Cloud

Ximalaya AI Cloud leverages DeepRec’s Embedding Variable to elastically manage high‑dimensional sparse features with low collision, supporting admission/eviction, multi‑level storage and minute‑level incremental model updates, which together boost GPU utilization, halve training time and improve recommendation CTR by 2‑3 % while maintaining latency.

AI CloudDeepRecKubernetes
0 likes · 13 min read
DeepRec-Based High-Dimensional Sparse Feature Support and Real-Time Model Training in Ximalaya AI Cloud
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jul 22, 2023 · Artificial Intelligence

Building an Image Classification Model with Transformers and TensorFlow: Theory, Code, and Practice

This article explains how to leverage computer‑vision techniques and deep‑learning frameworks such as Transformers and TensorFlow to build a complete image‑classification pipeline, covering the underlying RGB and CNN principles, model architecture, data preparation, training, and inference with runnable Python code.

CNNPythonTensorFlow
0 likes · 15 min read
Building an Image Classification Model with Transformers and TensorFlow: Theory, Code, and Practice
WeiLi Technology Team
WeiLi Technology Team
May 8, 2023 · Artificial Intelligence

How to Run GPT‑2 Locally: Complete Setup and Code Adjustments

This guide explains the GPT‑2 background, required software, environment configuration, code modifications for TensorFlow 2.x, data download, execution commands, and sample test results, providing a full step‑by‑step process for local deployment of the model.

AIGPT-2Local Deployment
0 likes · 7 min read
How to Run GPT‑2 Locally: Complete Setup and Code Adjustments
DataFunTalk
DataFunTalk
Mar 15, 2023 · Artificial Intelligence

Predicting Sunspot Activity with CnosDB and a TensorFlow 1DConv‑LSTM Model

This article demonstrates how to store monthly sunspot numbers in the CnosDB time‑series database and use TensorFlow to build a 1DConv‑LSTM neural network for forecasting sunspot activity, covering data import, database insertion, train‑test splitting, model definition, training, and result visualization.

1DConv LSTMCnosDBPython
0 likes · 11 min read
Predicting Sunspot Activity with CnosDB and a TensorFlow 1DConv‑LSTM Model
Alimama Tech
Alimama Tech
Mar 14, 2023 · Artificial Intelligence

Neural Approximate Nearest Neighbor (NANN): Open‑Source Large‑Scale Retrieval with Arbitrary Complex Models

Alibaba’s open‑source Neural Approximate Nearest Neighbor (NANN) library decouples index learning from model training, enabling any TensorFlow‑based deep model to perform high‑throughput, high‑accuracy HNSW‑based retrieval with GPU multi‑streaming, XLA acceleration, graph optimizations, and adversarial training that mitigates L2‑distance mismatch, all supported by ready‑to‑use benchmarks and demos.

Neural ANNOpen-sourceTensorFlow
0 likes · 7 min read
Neural Approximate Nearest Neighbor (NANN): Open‑Source Large‑Scale Retrieval with Arbitrary Complex Models
Laiye Technology Team
Laiye Technology Team
Feb 17, 2023 · Artificial Intelligence

Understanding Diffusion Models, Autoencoders, and VAEs for AIGC with Code Examples

This article introduces the hot AIGC field by explaining diffusion‑based image generation, detailing the principles and mathematics of AutoEncoder and Variational AutoEncoder models, and providing complete TensorFlow code examples to help readers master these generative techniques step by step.

AIGCTensorFlowautoencoder
0 likes · 8 min read
Understanding Diffusion Models, Autoencoders, and VAEs for AIGC with Code Examples
DataFunSummit
DataFunSummit
Nov 19, 2022 · Operations

Large-Scale Supply Chain Inventory Optimization Using Recurrent Neural Networks

This article presents a novel approach that leverages recurrent neural network techniques and TensorFlow to dramatically accelerate simulation and optimization of massive supply‑chain networks, enabling efficient inventory positioning and safety‑stock decisions for networks with hundreds of thousands of items.

TensorFlowinventory optimizationlarge-scale computing
0 likes · 13 min read
Large-Scale Supply Chain Inventory Optimization Using Recurrent Neural Networks
Dada Group Technology
Dada Group Technology
Nov 18, 2022 · Artificial Intelligence

JD Daojia Machine Learning Platform: Architecture and Implementation

This article introduces JD Daojia's machine learning platform, detailing its architecture, implementation principles, and practical applications in various business scenarios, achieving significant improvements in recommendation and search systems.

Feature EngineeringGraph Neural NetworksKubernetes
0 likes · 28 min read
JD Daojia Machine Learning Platform: Architecture and Implementation