NumPy is an open source library for the Python programming language, adding support for large, multidimensional arrays, and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
Personal tasks or codes of Machine Learning and Artificial Intelligence
This project is designed to be a AIaaS 2-Way-PMS optimized with AI and ML models
This Repository will contain Source Code of Projects that I have done in CodeAlpha Internship
This project analyzes a Kaggle depression dataset using data preprocessing, clustering, classification, and outlier detection techniques
Predicting real estate house prices using various machine learning algorithms, including data exploration, preprocessing, model training, and evaluation
ML based project which uses various techniques to build a hybrid model for identifying brain tumour in MRI images
Galaxy Classification is a machine learning project focused on classifying galaxies into two subclasses: 'STARFORMING' and 'STARBURST'
A collection of machine learning projects featuring models and algorithms for supervised and unsupervised learning, model evaluation, and optimization
A university project related to data mining lesson on StackOverflow website data with Python language
This repository contains a project that demonstrates how to perform sentiment analysis on Twitter data using Apache Spark, including data preprocessing, feature engineering, model training, and evaluation
datascienv is package that helps you to setup your environment in single line of code with all dependency and it is also include pyforest that provide single line of import all required ml libraries
The aim of this project is to develop a solution using Data science and machine learning to predict the compressive strength of a concrete with respect to the its age and the quantity of ingredients used
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques
Technical and sentiment analysis to predict the stock market with machine learning models based on historical time series data and news article sentiment collected using APIs and web scraping