Deep Learning > TensorFlow
Library for machine intelligence.
Contents
Tutorials
From the basics to slightly more interesting applications of TensorFlow
Introduction to deep learning based on Google's TensorFlow framework. These tutorials are direct ports of Newmu's Theano
These tutorials are intended for beginners in Deep Learning and TensorFlow with well-documented code and YouTube videos.
TensorFlow tutorials written in Python with Jupyter Notebook
Re-create the codes from other TensorFlow examples
TensorFlow compiled and running properly on the Raspberry Pi
Recurrent Neural Network classification in TensorFlow with LSTM on cellphone sensor data
Learn to use a seq2seq model on simple datasets as an introduction to the vast array of possibilities that this architecture offers
SIRDS is a means to present 3D data in a 2D image. It allows for scientific data display of a waterfall type plot with no hidden lines due to perspective.
Models/Projects
A simple and well-designed template for your tensorflow project.
Implementation of Unsupervised Cross-Domain Image Generation
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
An implementations of AlexNet3D. Simple AlexNet model but with 3D convolutional layers (conv3d).
Annotated notes and summaries of the TensorFlow white paper, along with SVG figures and links to documentation
An attempt to implement the random handwriting generation portion of Alex Graves' paper
Search, filter, and describe videos based on objects, places, and other things that appear in them
This performs a monolingual translation, going from modern English to Shakespeare and vice-versa.
Unsupervised Image to Image Translation with Generative Adversarial Networks
Neural Network to colorize grayscale images
Implementation of "Show, Attend and Tell"
Implementation of "Learning Deep Features for Discriminative Localization"
Implementation of viterbi and forward/backward algorithms for HMM
Train TensorFlow neural nets with OpenStreetMap features and satellite imagery.
TensorFlow implementation of DeepMind's 'Human-Level Control through Deep Reinforcement Learning' with OpenAI Gym by Devsisters.com
TensorFlow implementation of "Training Very Deep Networks" with a blog post
TensorFlow implementation of "Hierarchical Attention Networks for Document Classification"
TensorFlow implementation of "Convolutional Neural Networks for Sentence Classification" with a blog post
TensorFlow implementation of Character-Aware Neural Language Models
TensorFlow implementation of 'YOLO: Real-Time Object Detection', with training and an actual support for real-time running on mobile devices.
This is a TensorFlow implementation of the WaveNet generative neural network architecture for audio generation.
Tensorflow implementation of "Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment"
Tensorflow implementation of "Visualizing and Understanding Convolutional Networks"
Tensorflow implementation for MIT "Generating Videos with Scene Dynamics" by Vondrick et al.
Implementation of "3D Convolutional Neural Networks for Speaker Verification application" in TensorFlow by Torfi et al.
TensorFlow Implementation of "Cross Audio-Visual Recognition in the Wild Using Deep Learning" by Torfi et al.
Implementation of "Hierarchical Attentive Recurrent Tracking"
Implementation of Holographic Embeddings of Knowledge Graphs
A simple embedding based text classifier inspired by Facebook's fastText.
Classify music genre from a 10 second sound stream using a Neural Network.
Powered by TensorFlow
Libraries
Implementation of Monotonic Calibrated Interpolated Look-Up Tables in TensorFlow
Deep learning and reinforcement learning library for researchers and engineers
TensorForce: A TensorFlow library for applied reinforcement learning
initiative from Yahoo! to enable distributed TensorFlow with Apache Spark.
Simple framework allowing to read-in ROOT NTuples by converting them to a Numpy array and then use them in Google Tensorflow.
Sonnet is DeepMind's library built on top of TensorFlow for building complex neural networks.
Neural Network Toolbox on TensorFlow focusing on training speed and on large datasets.
Layer on top of TensorFlow for doing machine learning on encrypted data
Machine Learning on Graphs, a Python library for machine learning on graph-structured (network-structured) data.
High-Level Keras Complement for implement common architectures stacks, served as easy to use plug-n-play modules
TensorLayerX: A Unified Deep Learning Framework for All Hardwares, Backends and OS, including TensorFlow.
Papers
Globally Normalized Transition-Based Neural Networks
Tools/Utilities
Automatically apply SOTA optimization techniques to achieve the maximum inference speed-up on your hardware.
Videos
Diving into Machine Learning through TensorFlow
Books
by Dr. Chris A. Mattmann, Chief Data and Artificial Intelligence Officer at UCLA and author also of Tika in Action. This book makes the math-heavy topic of AI and ML approachable and practicle to a newcomer. Updated to Tensorflow2 and the latest version of this book.