Tensorflow Libraries - Page 1

An Open Source Machine Learning Framework for Everyone

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🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

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Models and examples built with TensorFlow

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Deep Learning for humans

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Deepfakes Software For All

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TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

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DeepFaceLab is the leading software for creating deepfakes.

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YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

Python 39392Updated: 1 y ago License: Strong Copyleft (AGPL-3.0)

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

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TensorFlow code and pre-trained models for BERT

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Caffe: a fast open framework for deep learning.

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Google Research

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AI-Powered Photos App for the Decentralized Web 🌈💎✨

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DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

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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, AWS, and various command lines.

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⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.

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A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

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Visualizer for neural network, deep learning, and machine learning models

JavaScript 23143Updated: 1 y ago License: Permissive (MIT)

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

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An open autonomous driving platform

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Deezer source separation library including pretrained models.

Python 22739Updated: 1 y ago License: Permissive (MIT)

A library for efficient similarity search and clustering of dense vectors.

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Cross-platform, customizable ML solutions for live and streaming media.

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DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.

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A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

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100-Days-Of-ML-Code中文版

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Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

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Create UIs for your machine learning model in Python in 3 minutes

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Magenta: Music and Art Generation with Machine Intelligence

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A WebGL accelerated JavaScript library for training and deploying ML models.

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Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

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ncnn is a high-performance neural network inference framework optimized for the mobile platform

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deep learning for image processing including classification and object-detection etc.

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《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning

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:satellite: Simple and ready-to-use tutorials for TensorFlow

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deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

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Best Practices on Recommendation Systems

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CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

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JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js

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Open standard for machine learning interoperability

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The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

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Open source platform for the machine learning lifecycle

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Datasets, Transforms and Models specific to Computer Vision

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A neural network that transforms a design mock-up into a static website.

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Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

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Image augmentation for machine learning experiments.

Python 13577Updated: 1 y ago License: Permissive (MIT)

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

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Face recognition using Tensorflow

Python 13092Updated: 1 y ago License: Permissive (MIT)

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

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Pretrained models for TensorFlow.js

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