Efficient sparse matrix implementation for various "Principal Component Analysis"

Several implementation of ML network embedding and graph embedding

poverty prediction and analysis

This is the basic introductory project of machine learning for predicting the survivals category based on the data set available,which is implemented using different inbuilt models available in scikit learn

Scikit-learn (sklearn) projects in form of Jupyter Notebooks

Hands on Tensorflow and Scikitlearn 2nd Edition eBook

Topics related to Machine Learning

Machine Learning Tutorials

Code samples for the machine learning algorithms that are explained in the book, "Hands-on Machine Learning with Scikit-Learn and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems"

A simple DNS atack detector based on DecisionTree built with scikit-learn

A collection of documents and programs to learn about Data Science and ML using Scikit-learn.

Decision tree implementation using python scikit-learn

This repository includes my House Prices Multi-Variate Linear Regression-Flatiron School Module 2 Project. In this project I made use of the OSEMN methodology incorporating packages such as Pandas, NumPy, Matplotlib, Seaborn, and Scikit-Learn.

Machine learning using sci kit learn

This repository contains the code for some models that classify music files into their specific genres

simple classification of hanzi by scikit-learn

This repository demonstrates data imputation using Scikit-Learn's SimpleImputer, KNNImputer, and IterativeImputer.

This repository demonstrates the scaling of the data using Scikit-learn's StandardScaler, MinMaxScaler, and RobustScaler.

This repository demonstrates reducing the dimensions of the dataset using Scikit-learn's Principal Component Analysis (PCA) and T-distributed Stochastic Neighbor Embedding (t-SNE).