Python Package for Empirical Statistical Downscaling. pyESD is under active development and all colaborators are welcomed. The purpose of the package is to downscale any climate variables e.g. precipitation and temperature using predictors from reanalysis datasets (eg. ERA5) to point scale. pyESD adopts many ML and AL as the transfer function.

A Deep Learning based Fashion Recommendation System using the ResNET50

This is a repository to learn and get more computer vision skills, make robotics projects integrating the computer vision as a perception tool and create a lot of awesome advanced controllers for the robots of the future.

Thesis project: topic categorization and sentiment analysis on twitter with Apache Spark

Building a Machine Learning Library from scratch using Python3, based on SOTA library Scikit-learn

Free High-Quality Financial Data in Azure

A shoe👟 recommendation website.

Model bank customers behaviour. Publish findings on an online dashboard.

Quantitative analysis CLI for Forex and Cryptocurrencies.

This project is designed to extract sales data from a PostgreSQL database, process it, and use a Random Forest model to predict sales quantities. It also visualizes real and predicted sales for better understanding.

implementation of of a program who classify text documents into classes according to their content - Machine learning

This is a python Flask web app made to predict the house prices based on attributes like no. of rooms, parking facility, etc. The prediction algorithm used at the backend is 'Linear Regression'.

A project exploring various classification algorithms, showcasing their implementation, comparison, and evaluation using Python and scikit-learn.

This Python code represents a machine learning project that builds a simple linear regression model using experience and salary data. It plots the data, constructs the regression model, and visualizes the results.

Experiment with machine learning and AI algorithms, write guides, and documents.

This repository contains a model built using python and Logistic Regression algorithm

This Model was built using Python and Linear Regression algorithm

This model was built using Python and KMeans Clustering algorithm