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

Data Engineering ZoomCamp

SigOpt wrappers for scikit-learn methods

CIFAR-10 Photo Classification

Python inverse kinematics for your robot model based on Pinocchio.

Code for the ICML 2021 paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision"

Medical image analysis framework merging ANTsPy and deep learning

Pynomial - a lightweight python library for implementing the many confidence intervals for the risk parameter of a binomial model

Existing Literature about Machine Unlearning

On the model-based stochastic value gradient for continuous reinforcement learning

Temporal Knowledge Graph Reasoning Triggered by Memories

BlockUnexpectedPackets - Preventing BungeeCord CPU overload due to Layer 7 DDoS attacks by scanning BungeeCord's logs

https://arxiv.org/abs/2102.11005

Code to replicate the key results from Exploring the Limits of Out-of-Distribution Detection

A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network"

maximal update parametrization (µP)

Sinkformers: Transformers with Doubly Stochastic Attention

Code release for BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images

Learning Features with Parameter-Free Layers (ICLR 2022)

pytorch implementation for PointNet

Bidimensional Leaderboards: Generate and Evaluate Language Hand in Hand