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

Caffe implementation for Hu et al. Segmentation for Natural Language Expressions

Probabilistic-Monocular-3D-Human-Pose-Estimation-with-Normalizing-Flows

Impelmentation for paper Feature Generation and Hypothesis Verification for Reliable Face Anti-Spoofing

Recovering Brain Structure Network Using Functional Connectivity

Tensorflow 2 Object Detection API kurulumu, GPU desteği, custom model hazırlama

Lightweight tool to perform MITM attack on local network

Official Pytorch implementation for "End2End Occluded Face Recognition by Masking Corrupted Features, TPAMI 2021"

Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"

Build upon neural radiance fields to create a scene-specific implicit 3D semantic representation, Semantic-NeRF

Learning trajectory representations using self-supervision and programmatic supervision.

Fusion-in-Decoder Distilling Knowledge from Reader to Retriever for Question Answering

PyTorch Implementation of Temporal Output Discrepancy for Active Learning, ICCV 2021

Using Streamlit to host a multi-page tool with model specs and classification metrics, while also accepting user input values for prediction.

This repository is a basic Machine Learning train & validation Template (Using PyTorch)

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

STARCH compuets regional extreme storm physical characteristics and moisture balance based on spatiotemporal precipitation data from reanalysis or climate model data.

Official implementation for “Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior”

This application is the basic of automated online-class-joiner(for YıldızEdu) within the right time. Gets the ZOOM link by scheduled date and time.

A PyTorch-centric hybrid classical-quantum machine learning framework

[CVPR 2020] Interpreting the Latent Space of GANs for Semantic Face Editing