TensorFlow Tutorials

You can find python source code under the python directory, and associated notebooks under notebooks.

	Source code	Description
1	basics.py	Setup with tensorflow and graph computation.
2	linear_regression.py	Performing regression with a single factor and bias.
3	polynomial_regression.py	Performing regression using polynomial factors.
4	logistic_regression.py	Performing logistic regression using a single layer neural network.
5	basic_convnet.py	Building a deep convolutional neural network.
6	modern_convnet.py	Building a deep convolutional neural network with batch normalization and leaky rectifiers.
7	autoencoder.py	Building a deep autoencoder with tied weights.
8	denoising_autoencoder.py	Building a deep denoising autoencoder which corrupts the input.
9	convolutional_autoencoder.py	Building a deep convolutional autoencoder.
10	residual_network.py	Building a deep residual network.
11	variational_autoencoder.py	Building an autoencoder with a variational encoding.

Installation Guides

For Ubuntu users using python3.4+ w/ CUDA 7.5 and cuDNN 7.0, you can find compiled wheels under the wheels directory. Use pip3 install tensorflow-0.8.0rc0-py3-none-any.whl to install, e.g. and be sure to add: export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64" to your .bashrc. Note, this still requires you to install CUDA 7.5 and cuDNN 7.0 under /usr/local/cuda.

Resources

Author

Parag K. Mital, Jan. 2016.

http://pkmital.com

License

See LICENSE.md

From the basics to slightly more interesting applications of Tensorflow

Related tags

Overview

TensorFlow Tutorials

Installation Guides

Resources

Author

License

Owner

Parag K Mital

TRACER: Extreme Attention Guided Salient Object Tracing Network implementation in PyTorch

Pytorch implementation of OCNet series and SegFix.

My published benchmark for a Kaggle Simulations Competition

The NEOSSat is a dual-mission microsatellite designed to detect potentially hazardous Earth-orbit-crossing asteroids and track objects that reside in deep space

SpeechBrain is an open-source and all-in-one speech toolkit based on PyTorch.

[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss

Container : Context Aggregation Network

A platform to display the carbon neutralization information for researchers, decision-makers, and other participants in the community.

Implementation of the CVPR 2021 paper "Online Multiple Object Tracking with Cross-Task Synergy"

This is an official pytorch implementation of Fast Fourier Convolution.

MT-GAN-PyTorch - PyTorch Implementation of Learning to Transfer: Unsupervised Domain Translation via Meta-Learning

基于tensorflow 2.x的图片识别工具集

ComPhy: Compositional Physical Reasoning ofObjects and Events from Videos

Implementation of Learning Gradient Fields for Molecular Conformation Generation (ICML 2021).

COPA-SSE contains crowdsourced explanations for the Balanced COPA dataset

A Python library for working with arbitrary-dimension hypercomplex numbers following the Cayley-Dickson construction of algebras.

A flag generation AI created using DeepAIs API

TransVTSpotter: End-to-end Video Text Spotter with Transformer

Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks

Official pytorch code for SSC-GAN: Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained Image Generation(ICCV 2021)