ACA-ML

A repository for the ACA project, done in 2015-16, my Sayash Kapoor and Kumar Kshitij Patel.

Work completed under this project :

• Read about various basic ML algorithms and techniques, including Linear Regression, Logistic Regression, SVMs, Neural Networks, Back-propagation, K-means clustering
• implemented 2 side projects: Sentiment analysis from movie reviews, and MNIST hand-wrtiting recognition
• Read papers about eigenfaces, PCA, Archetype analysis and SVD to gain a better understanding of how to implement face-recognition libraries

Code completed, studied and implemented:

• MNIST using SVMs
• MNIST using Neural Nets
• MNIST using linear regression on intensity
• Sentiment analysis of Movie reviews using Naive Bayes
• Naive Bayes
• Sentiment analysis using positive - negative word bag
• Stemming (NLTK Library)
• Spam Classifier using Naive Bayes
• Basic ML Algorithms, Andrew Ng

Tutorials completed:

• https://class.coursera.org/machlearning-001/lecture/241
• http://machinelearningmastery.com/naive-bayes-classifier-scratch-python/
• http://streamhacker.com/2010/05/10/text-classification-sentiment-analysis-naive-bayes-classifier/
• http://andybromberg.com/sentiment-analysis-python/