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An opinionated list of awesome Python frameworks, libraries, software and resources.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Models and examples built with TensorFlow
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
2023年最新总结，阿里，腾讯，百度，美团，头条等技术面试题目，以及答案，专家出题人分析汇总。
PyTorch Tutorial for Deep Learning Researchers
OpenMMLab Detection Toolbox and Benchmark
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…
Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
A complete and graceful API for Wechat. 微信个人号接口、微信机器人及命令行微信，三十行即可自定义个人号机器人。
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
State-of-the-art 2D and 3D Face Analysis Project
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Graph Neural Network Library for PyTorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
PyTorch implementations of Generative Adversarial Networks.
Datasets, Transforms and Models specific to Computer Vision
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
Bringing Old Photo Back to Life (CVPR 2020 oral)
Image augmentation for machine learning experiments.
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.
A MNIST-like fashion product database. Benchmark 👇
A paper list of object detection using deep learning.