Adit Deshpande

Machine learned bracketology

List of all the lessons learned, best practices, and links from my time studying machine learning

Sentiment Analysis with LSTMs in Tensorflow

Implementations of CNNs, RNNs, GANs, etc

Tutorial on GANs

Notes for several Machine Learning and Deep Learning courses, textbooks, and talks

Facebook chatbot that I trained to talk like me using Seq2Seq

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My notes from the classes I've taken at UCLA

The Flask server that communicates with my FB Messenger chatbot

Just trying to reimplement machine learning techniques like linear regression, neural nets, logistic regression, etc in Python

Neural network that predicts the number of wins for a baseball team based on the importance of different statistical categories and their influence on a team's success.

Tutorial on Using Pandas

Kaggle Competition for Predicting NCAA Basketball Tourney Games

Some scripts to get info from basketball-reference and then create CSVs on "basketball claims"

Build a Jekyll blog in minutes, without touching the command line.

Trying to apply deep learning to music analysis

CS 145 Yelp Project

Program that reads in accelerometer data (x, y, z direction values), trains a neural network program for classification, and then outputs predictions for a set of test data

Hackerrank ML Contest

Hackerrank ML Competition

Kaggle Competition for Predicting Interest of New Rental Listings

Trying out PyTorch because the hype is real

Programs with word vectors, RNN, NLP stuff, etc

Using the Quandl API to (try) to apply ML to the stock market

Repo for the $1.2 million Kaggle competition

Visualizations of statistics for NBA players

My Machine Learning + March Madness demo for UCLA's Tech+You event

Kaggle Ghosts ML Competition

Kaggle Titanic Survival ML Competition