Tensorflow
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An end-to-end deep learning library focused on clear code, speed, and research, built by Google Brain.
Go language bindings for OpenCV 4, enabling computer vision applications with support for CUDA, DNN, and OpenVINO.
A TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers with customizable neural layers.
A TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers, offering customizable neural layers.
A distributed caching platform that bridges computation frameworks and storage systems for large-scale analytics and ML workloads.
A suite of web applications for inspecting and understanding TensorFlow runs and graphs.
An open course on reinforcement learning with a practical focus, featuring hands-on labs and comprehensive materials for both online and on-campus students.
An open course on reinforcement learning with a practical focus, featuring hands-on labs and comprehensive materials for both online and on-campus students.
A high-performance neural network training interface for TensorFlow, optimized for speed and research flexibility.
A high-performance neural network training interface for TensorFlow focused on speed, flexibility, and reproducible research.
A TensorFlow implementation of YOLO for real-time object detection, supporting weight conversion, training, and mobile deployment.
An archived experiment integrating TensorFlow's machine learning capabilities directly into the Swift programming language with first-class differentiable programming.
A collection of simple tutorials introducing deep learning concepts using Google's TensorFlow framework.
A comprehensive toolset for converting, visualizing, and managing deep learning models across multiple frameworks like TensorFlow, PyTorch, and Caffe.
A TensorFlow implementation of a convolutional neural network for sentence classification based on Yoon Kim's paper.
A collection of TensorFlow tutorials covering basics to advanced neural network architectures with Python code and notebooks.
A Python library implementing state-of-the-art deep reinforcement learning algorithms with seamless Keras integration.
A TensorFlow implementation of neural style transfer that transforms images by applying artistic styles from one image to another.
Rust language bindings for TensorFlow, providing idiomatic access to machine learning capabilities.
A high-performance TensorFlow library for quantitative finance, providing mathematical methods, pricing models, and calibration tools.
A TensorFlow implementation of DeepMind's WaveNet neural network for generating raw audio waveforms.
DeepMind's library for building graph networks in TensorFlow and Sonnet, enabling graph-structured data processing with neural networks.
A compiler that extends SQL with AI capabilities to train, predict, and evaluate machine learning models directly from SQL statements.
Run trained Keras models directly in the browser with GPU acceleration via WebGL.
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
A Python module for easily training character- or word-level text-generating neural networks on any dataset with minimal code.
A modular container build system providing the latest AI/ML packages for NVIDIA Jetson and JetPack-L4T.
A collection of infrastructure and tools for research in neural network interpretability and visualization.
:earth_americas: Simple and ready-to-use tutorials for TensorFlow
Official code repository for the 'Machine Learning with TensorFlow' book with practical examples.
A library for probabilistic reasoning and statistical analysis integrated with TensorFlow and JAX.
A web application for training deep learning models with a focus on computer vision tasks.
A research framework for reinforcement learning providing modular building blocks and reference agent implementations.
Enables distributed TensorFlow training and inferencing on Apache Spark and Hadoop clusters with minimal code changes.
An open-source platform for building, training, and monitoring large-scale deep learning applications with full lifecycle MLOps.
A TensorFlow project template with a well-designed folder structure and OOP design to accelerate deep learning development.
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