Repo-2017

Why we included this project

This repository is essentially one practitioner's working notebook of experiments across applied data science, and for learners it beats abstract theory because every script is real, runnable code. Each file handles a single self-contained task: sentiment analysis on movie reviews, topic modeling over Wikipedia pages, autoencoder reconstruction of audio, time-series forecasting, and a few recommender and classification problems. You can open one file, run it against the bundled dataset, and trace exactly how the model is built. The collection is broad, giving you many small, reproducible starting points in NLP, computer vision, and classical machine learning, all in plain Python with Keras, Theano, and Gensim. Just keep in mind the code targets an older Keras version and was never meant to be maintained software, so treat it as a study reference and a source of ideas to port into your own stack.