Machine-learning-labs

This repository includes implementation of different machine learning algorithms in python

• Lab_1 : Linear Regression through exact form

• Lab_2 : Exploratory Analysis on a real-world dataset from Rossman GmbH using Pandas and Matplotlib, Linear Regression via Gaussian Elimination and Multivariate Autoregressive

• Lab_3 : Gradient Descent on Rosenbrock function, Linear Regression with Gradient Descent and Steplength controlling algorithms like backtracking, bolddriver for Gradient Descent

• Lab_4 : Dataset preprocessing, Logistic Regression with Gradient Descent and Newton Algorithm

• Lab_5 : Backward search for variable selection on Bank marketing dataset, Regularization for Logistic Regression and state-of-the-art Hyperparameter Optimization algorithm (Hyperband) for tuning the hyperparameters

• Lab_6 : Dataset Preprocessing, Generalized Linear Models with Scikit Learn, Higher Order Polynomial Regression and Coordinate Descent algorithm

• Lab_7 : Dataset Preprocessing on University of California, Riverside’s Time Series Classification Dataset, Dataset Imputation with K-Nearest Neighbour algorithm, Time Series Classification with Various Distance Measures and Accelerating K-Nearest Neighbour Classifier using Partial Distances/Lower Bounding, Locality Sensitive Hashing

• Lab_8 : Optical Character Recognition via Neural Networks, End-to-End Self-Driving via Convolutional Neural Networks, Implementation of the Convolutional Neural Network Architecture proposed in the paper titled, "End to End Learning for Self-Driving Cars", Hyperparameter Tuning, Regularization with Image Transformations

• Lab_9: Implementation of Decision Tree with different Quality-criterion, Gradient Boosted Decision Trees

• Lab_10: Exploring Movie Recommendation Datasets like movielens 100k dataset, Implementing basic matrix factorization (MF) technique for recommender systems, Recommender Systems using matrix factorization sckitlearn

• Lab_11: Preprocessing 20newsgroups dataset, Implementing Naive Bayes Classifier for Text Data, Implementing SVM Classifier via Scikit-Learn