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

Simulation of self-focusing of laser beams in condensed media

DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data.

Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course

[ICCV 2021] HRegNet: A Hierarchical Network for Large-scale Outdoor LiDAR Point Cloud Registration

Multi-objective gym environments for reinforcement learning.

MG-GCN: Scalable Multi-GPU GCN Training Framework

The pytorch implementation of the paper "text-guided neural image inpainting" at MM'2020

The Surprising Effectiveness of Visual Odometry Techniques for Embodied PointGoal Navigation

Node-level Graph Regression with Deep Gaussian Process Models

Learning Versatile Neural Architectures by Propagating Network Codes

Scheduling BilinearRewards

TumorInsight is a Brain Tumor Detection and Classification model built using RESNET50 architecture.

一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM，xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,AFN,ONN,DIN, DIEN ... （pytorch, tf2.0）

This is the official PyTorch implementation for "Mesa: A Memory-saving Training Framework for Transformers".

This is a file about Unet implemented in Pytorch

The official repo of the CVPR2021 oral paper: Representative Batch Normalization with Feature Calibration

Few-NERD: Not Only a Few-shot NER Dataset

Keqing Chatbot With Python

Code for the paper "Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness"

This is the pytorch implementation of the paper - Axiomatic Attribution for Deep Networks.