An open-source machine learning framework for everyone.

TensorFlow™ is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google’s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains.

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TensorFlow 2019 Projects

  • Param Bhavsar
    Add traditional machine learning algorithms to the Swift TensorFlow library
    This document describes the proposal to "add traditional Machine Learning algorithms to the Swift TensorFlow library", for "TensorFlow" organization....
  • whiterat
    Adding and standardizing image processing operations in tf.image
    Project aims at updating existing functions to make them compatible with Tensorflow 2.0 and adding new image processing operations to make the...
  • Ryan Lee
    Adding Curiosity to TF-Agents
    Reinforcement learning is a class of machine learning methods that use the reward signal of the environment to infer optimal actions. Thus, easy...
  • Victor Antony
    Adding traditional Machine Learning algorithms to Swift for Tensorflow
    This project aims to add traditional machine learning algorithms to the Tensorflow for Swift library. We aim to implement Logistic Regression,...
  • snowkylin
    An Extended Version of “A Concise Handbook of TensorFlow” And A Library of Extended Keras Layers for TF 2.0
    Usability and 3rd cutting-edge models are two main factors that are especially concerned by academic area. This project concentrate on enhancing both...
  • Vishal V
    Core Model Migration to TF 2.0
    Re-building the official Tensorflow models to make it TF 2.0 compatible. This project proposes holistic improvements to the models repository to...
  • Paul Pauls
    Creating Neuroevolution Framework for Tensorflow 2.0, preimplementing 'Neuroevolution of Augmenting Topologies' (NEAT)
    Implementing a framework for Neuroevolution in Tensorflow 2.0, providing a variety of preimplemented Neuroevolution algorithms, genomes and...
  • Karthik Ramesh Iyer
    Data Visualization library for Swift
    Swift for TensorFlow is a Swift library that helps develop and train ML models. Data Visualization can be helpful when exploring a dataset. It helps...
  • Bruna Pinos
    Debugging Model Performance in TensorBoard Guide
    TensorBoard is a TensorFlow tool for models visualization. It can generate histograms, graph and help debug and improve the neural network. To help...
  • Ayush Agrawal
    End-to-End Mobile Swift for Tensorflow Application
    Deploying a machine learning module using Swift for Tensorflow it to a mobile device, including building out necessary components of the Swift for...
  • Chanchal Kumar Maji
    Improving and adding more functionality to the TensorFlow-Datasets library with the addition of DatasetBuilders for important research datasets.
    Tensorflow Datasets or tfds makes the work of the user easier by transforming the raw dataset into a standard format so that it can be immediately...
  • Jiacheng Xu
    JSON Dataset Reader - TensorFlow I/O
    TensorFlow is one of the most popular machine learning frameworks and is widely used in fields beyond machine learning and data science. The...
  • Sasha Illarionov
    Reasonable Effectiveness of Mobile Inference: Adaptive Growth of the TensorFlow.js Model Garden
    The project aims to grow the TensorFlow.js model garden with five new low-latency, low-power, high-accuracy applications controlled via an...
  • Recep Ahmet SARITEKIN
    TensorFlow Datasets - Implement new features in TFDS for users and developers
    Main goal of this project is extending available datasets, offering some additional features to Tensorflow Datasets that can make TensorFlow users'...
  • Adrish Dey
    TensorFlow Hub Module Creation and Support for TensorFlow.js
    Training of High end Deep Learning Models takes a Long time to Train, Hours, Days and Even Weeks. So, as a Developer/researchers it slows down the...
  • Paul Spende
    TensorFlow js Exploration
    This project will convert some pre-trained Keras models into TensorFlow js models and explains how they can be made accessible by packing them in npm...
  • ace
    TensorFlow Official Model Migration to v2.0
    Migration of official TensorFlow models to use/support TF v2.0 features/functions.
  • Wenhe Li
    TensorFlow.js with WebWorker
    The TensorFlow.js will be highly computational consuming while we are doing prediction or classification. And if such a computation happens at the UI...
  • Tasmiah Tahsin Mayeesha
    Text embedding modules in tensorflow hub
    Project's main goal is adding new techniques and tools for text embedding modules in TensorFlow Hub.It is divided into three parts: Improve the...