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.

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.

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

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.

tracebloc data pipeline for training/test dataset setup

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

This is a simple ANN deep learning classification technique

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.

Natural LangWiz is a repository for exploring Natural Language Processing (NLP) techniques through Jupyter notebooks. It covers everything from text preprocessing and sentiment analysis to advanced transformer models. Dive in to see how we turn raw text into actionable insights with a touch of NLP wizardry!

This repository contains an in-depth analysis of historical weather data from Szeged, Hungary. The project uses Python to clean and process data, generate insightful visualizations, and identify patterns and correlations in weather parameters such as temperature, humidity, and precipitation.

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.

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 Science Projects

A simplification and extension of the Data Prep Kit project

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.

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.

This is an exciting project that aims to predict cryptocurrency prices using artificial intelligence (AI) and machine learning (ML) techniques. The project uses historical data of various cryptocurrencies and applies different algorithms to predict their prices in the future.

This project analyzes sales, profit, and quantity trends across different product categories in a superstore dataset (2011-2014) using Python, Pandas, Matplotlib, and Seaborn. It provides data-driven insights through visualizations to optimize business strategies.

This repository contains an analysis of the Kaggle Machine Learning & Data Science Survey dataset, focusing on salary prediction using ordinal logistic regression and other classification models.