Small scale machine learning projects to understand the core concepts
- Topic Modelling using Latent Dirichlet Allocation with newsgroups20 dataset, implemented with Python and Scikit-Learn
- Implemented a simple neural network built with Keras on MNIST dataset
- Stock Price Forecasting on Google using Linear Regression
- Implemented a simple a social network to learn basics of Python
- Implemented Naives Bayes Classifier to filter spam messages on SpamAssasin Public Corpus
- Churn Prediction Model for banking dataset using Keras and Scikit-Learn
- Implemented Random Forest from scratch and built a classifier on Sonar dataset from UCI repository
- Simple Linear Regression in Python on sample dataset
- Multiple Regression in Python on sample dataset
- PCA and scaling sample stock data in Python [working_with_data]
- Decision Trees in Python on sample dataset
- Logistic Regression in Python on sample dataset
- Built a neural network in Python to defeat a captcha system
- Helper methods include commom operations used in Statistics, Probability, Linear Algebra and Data Analysis
- K-means clustering with example data; clustering colors with k-means; Bottom-up Hierarchical Clustering
- Generating Word Clouds; Sentence generation using n-grams; Sentence generation using Grammars and Automata Theory; Gibbs Sampling; Topic Modelling using Latent Dirichlet Analysis (LDA)