TensorFlow Input Pipeline Examples based on multi-thread and FIFOQueue

Mini-batch SVM / Logistic Regresion, Online learning for large scale data.

A repo holding the implementation as well as some theoretical explanation of the important relevant concepts. It is going to be in development for a long long time. I'll keep adding things everytime I have something to add to it, and I have the time for it. One can use it to learn the basics of Machine Learning from kind of scratch.

Tensorflow implementation of asyncronous 1-step Q learning in "Asynchronous Methods for Deep Reinforcement Learning" with improvement on weight update process (use minibatch) to speed up training.

Demonstration of generating mini-batches in Tensorlfow from GPU memory.

Usefull python implementation of batch iterator.

Graph Attention-based Instance Selection (GAIS). Python package for a novel instance selection method utilizing graph attention networks.

This is an implementation of different optimization algorithms such as: - Gradient Descent (stochastic - mini-batch - batch) - Momentum - NAG - Adagrad - RMS-prop - BFGS - Adam Also, most of them are implemented in vectorized form for multi-variate problems

Provides a basic edge simulator

Examples of Linear Regression and three Gradient Descent methods (Batch, Stochastic and Mini-Batch)

Use of various deep learning models to classify flowers. Models are implemented from scratch in PyTorch using only tensor operations.

Predict airplane's status by implementing Linear Regression with Regularization, Batch/ Mini-Batch/ Stochastic Gradient Descent.