Data Science and Machine Learning

Basic machine learning and deep learning models and datasets

#Projects updated till now

1. Classification problem using scikit-learn and KNeighbors approach on iris dataset
2. Linear Regression on Combined cycle power plant dataset using Ridge and Lasso
3. Classification on Haberman's Survival dataset using Logisitic Regression
4. Ridge Linear Regression analysis on Computer hardware dataset to estimate the relative performance of devices as per its specifications.
5. Predicting annual income of a person using Support Vector Classification
6. Unsupervised Learning using KMeans algorithm on 3D Road n/w dataset
7. NLP:Natural Language Processing- classification of 20 news groups from news articles (Text Classification)
8. Association Learning: A very simple association learning usage example on a transaction details dataset of a market.
9. Dimensionality Reduction examples: PCA / LDA / Kernel PCA
10. Deep Learning: Handwriting recognition(Image classification) on MNIST dataset using Keras
11. Artificial Neural Network to predict the behaviour of bank's customers
12. Convolutional Neural Network to predict different fashion items. (99% accuracy on MNIST digits dataset with this same model)
13. Recurrent Neural Network (LSTM) to predict BTC-INR stock prices for the month of April-May 2018
14. Stacked Auto Encoder (PyTorch): Movies Recommendation System on dataset provided by movieslens