Awesome

Advanced Machine Learning Related Projects

This is a collection of ML projects that I did, topics include:

Regression: Linear Regression, Lasso, Ridge
Time Series: ARIMA, SARIMA (Box-Jenkins Approach), Exponential Smoothing (Holt-Winters Approach), VAR, VARX (Vector Autoregression Approach) etc
Recommender System: collaborative filtering and matrix factorization
NLP: embeddings, Tf-idf etc
XGBoost, Random Forest implementation
Neural Network: Image classification

Here's an Ad, are you gonna click it?

Use Random Forest with feature engineering to predict Click-Through Rate (CTR) with Avazu data. Final result with Log Loss ≈ 0.4.

Stop Spamming my Email!

Use Adaboost and XGBoost methods to predict if a email is a spam with 97% accuracy rate.

Teach Computers to recognize Digits

Pytorch: implement simple 2-Layer and 3-Layer neural network using MNIST dataset to predict hand written digit with an accuracy rate of 98.29%

So you watched a movie: Yay or Nay?

Use Glove embeddings on movie review dataset of 50,000 reviews from IMDB. Predict if a review is positive or negative given the content: use XGBoost to achieve an 86.7% accuracy rate.

How much is my House Worth?

Use Linear Regression to predict the house prices in Ames, Iowa. Compare regression models of OLS, Ridge, Lasso and Elastic Net techniques and generate a business report.

BBC Article Recommendations

Replicate the recommendation system on blog-based website: provide 5 articles based on what the user is reading now using word2vec on data.

Build your own Netflix recommendation engine!

Build a movie rating recommendation system from scratch using collaborative filtering with matrix factorization.

Twitter Sentiment Analysis!

I know, I know, I know. You've seen this project a million times, as a ML student, I just had to do it like everyone else :)

Part of the code is modified from Prof. Yannet Interian's USF Advanced ML class. Part of the code is modified from Prof. Terence Parr's USF data acquisition class..