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accel-brain-code

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

arduinosourcecode

boltzmann-machines

Boltzmann Machines in TensorFlow with examples

data-scientist-roadmap

Toturials coming with the "data science roadmap" picture.

dwave-neal

An implementation of a simulated annealing sampler for general Ising model graphs in C++ with a dimod Python wrapper.

interviews.ai

It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.

pegasusdraw

This the code given in Dattani paper to be used to Draw Pegasus Layout

qite

rbm

Some python code for playing with Restricted Boltzmann Machines

rbm-ae-tf

Tensorflow 1.X implementation of Restricted Boltzman Machine(RBM) and Autoencoder with layerwise pretraining.

shark

The Shark Machine Leaning Library. See more:

smartphone-antenna-characterization

tensorfow-rbm

Tensorflow implementation of Restricted Boltzmann Machine

tf_quantum

Hybrid Quantum-Classical Machine Learning in TensorFlow

tfq-varqbm

Variational quantum Boltzmann machine and variational quantum imaginary time evolution built with Cirq and Tensorflow Quantum