Embark on a transformative "100 Days of Machine Learning" journey. This curated repository guides enthusiasts through a hands-on approach, covering fundamental ML concepts, algorithms, and applications. Each day, engage in theoretical insights, practical coding exercises, and real-world projects. Balance theory with hands-on experience.

tracebloc data pipeline for training/test dataset setup

This is a Movie Recommendation System that suggests movies to users based on their preferences. The system uses machine learning techniques to recommend similar movies.

In this ML project i have used Natural language processing (NLP) techniques and other data preprocessing techniques to feed my Machine Learning Algorithm a good data, and deploy it using flask.

A small library with Pandas-like api used for function ops execution and data transforms.

a impactful repository of predicting , analyzing the real-time groundwater levels , allowing simplified and modern way for researchers to analyze ground water levels .

Create the Decision Tree classifier and visualize it graphically. The purpose is if we feed any new data to this classifier, it would be able to predict the right class accordingly.

Improving credit risk model using Machine learning techniques. We use a host of ml models and neural network to solve the issue.

This is a simple ANN deep learning classification technique

AI-powered stock insights for Indian (NSE) stocks. Features machine learning predictions with 99 technical + fundamental features, real-time data from Yahoo Finance, and a modern React frontend.

A collection of hands-on solutions for checkpoints in a machine learning course. Covers core ML concepts such as data preprocessing, model training, and evaluation using Scikit-learn, with practical implementation on various datasets.

A project on visualizing and analyzing sales, revenue, and profit data across different markets from 2017 to 2020(India).

Data Science Projects

E-commerce Return Rate Reduction Analysis – Data-driven project using SQL, Python (Logistic Regression), and Power BI to analyze return patterns, predict customer behavior, and provide actionable insights to reduce product returns.

This project focuses on detecting and localizing copy-move forgery in digital images using Python. Deep learning techniques are applied to identify duplicated regions within an image. The model highlights tampered areas, helping verify the image's authenticity.

The Traffic Accident Prediction project aims to develop a system that predicts accident likelihood and severity using historical data. It provides insights to authorities and the public to enhance road safety and reduce accident costs.

Forecasted Airbnb 'Super host' status in Chicago with an 84% accuracy using Logistic Regression and assessed potential returns on investment employing the Herfindahl Index for strategic investment insights

Data analysis and machine learning project focused on assessing water quality using Decision Tree and Random Forest models

An end-to-end machine learning project that predicts anxiety severity using classification models (Naive Bayes, Decision Tree, SVM, Logistic Regression, XGBoost), based on lifestyle, health, and behavioral features.