samridhishree / Deeplearning-Models

Deep learning models in Python

mlp-classifier restricted-boltzmann-machine autoencoder autoencoder-mnist language-modeling word2vec batch-normalization neural-language-model denoising-autoencoders multilayer-perceptron-network multilayer-network

Topics in Deep Learning

This repository contains the implementations for the course “Topics in Deep Learning” @ CMU (10-707). All the implementations are in python.

Multi-Layer Perceptron:

Implement a multi-layer neural network with different activation funcations and mini-batched data with batch normalisation.

Restricted Boltzmann Machine (RBM) and Autoencoder:

Implement a Restricted Boltzmann Machine and an Autoencoder and use them as pre-trainers for the input to the MLP.

Neural Language Model:

Build a 4-gram Neural Language Model and interpret the word vectors learnt from it.

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Deep learning models in Python

mlp-classifier restricted-boltzmann-machine autoencoder autoencoder-mnist language-modeling word2vec batch-normalization neural-language-model denoising-autoencoders multilayer-perceptron-network multilayer-network

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