Machine Learning Projects

Build a Collaborative Filtering Recommender System in Python

Learn how to create a personalized movie recommendation system using SVD, LightFM, collaborative filtering, and weighted ratings for accurate and scalable suggestions.

Time Series Analysis with Facebook Prophet Python and Cesium

Forecast healthcare call volumes using Prophet with enhanced features from Cesium. Improve accuracy with statistical features and seasonal patterns.

Build ARCH and GARCH Models in Time Series using Python

This project forecasts stock market volatility using ARCH and GARCH models, helping traders and investors predict market changes and manage financial risks effectively.

Machine Learning Deep Learning

Build A Book Recommender System With TF-IDF And Clustering(Python)

Create a book recommendation system with machine learning using TF-IDF, KMeans clustering, and cosine similarity for accurate, data-driven suggestions

Machine Learning Deep Learning

Build Multi-Class Text Classification Models with RNN and LSTM

Multi-class text classification using RNN and LSTM for analyzing customer complaints, and providing real-world business insights and solutions.

Time Series Forecasting with ARIMA and SARIMAX Models in Python

Build and assess time series forecasting models such as ARIMA, ARIMAX, and SARIMAX using real-world data from sectors like Healthcare and Banking for precise predictions.

Build an Autoregressive and Moving Average Time Series Model

Clean and analyze IoT sensor data by building and evaluating MA and AR models, using RMSE and visualizations to determine the best forecasting model.

Time Series Forecasting Using Multiple Linear Regression Model

Understand time series forecasting with Linear Regression, ARIMA, and anomaly detection. Learn feature engineering, trend analysis, and model evaluation effectively.

Time Series Analysis and Prediction of Healthcare Trends Using Gaussian Process Regression

Predict Healthcare trends using Gaussian Process Regression. Understand preprocessing, modeling, and evaluation techniques for precise time-series forecasting results.

Sentiment Analysis for Mental Health Using NLP & ML

Classify mental health statements using NLP and ML techniques. Includes preprocessing, TF-IDF, XGBoost, Random Over-Sampling, and real-world prediction applications.

Credit Card Default Prediction Using Machine Learning Techniques

Preprocess data, engineer features, and apply models like Random Forest or XGBoost. Evaluate performance and use LIME/SHAP for interpretability.

Build Regression Models in Python for House Price Prediction

Build a model to predict house prices using Linear Regression. Understand data cleaning, feature selection, and model evaluation for accurate price forecasts.

Build a Customer Churn Prediction Model using Decision Trees

Predict customer churn with Decision Trees! Learn data cleaning, SMOTE, and model evaluation using Python. Compare Decision Tree and Logistic Regression models to find the best approach in this hands-on, beginner-friendly project.

Build Regression (Linear, Ridge, Lasso) Models in NumPy Python

Build and evaluate regression models (Linear, Lasso, Ridge) to predict laptop prices with effective data preprocessing and performance metrics.

Word2Vec and FastText Word Embedding with Gensim in Python

Understand how CBOW, Skip-Gram, and FastText models capture word meanings, visualize embeddings, and evaluate model performance for various NLP tasks.

BigMart Sales Prediction ML Project in Python

Learn retail sales prediction with machine learning. This project builds regression models to analyze sales trends and drive data-driven decisions for retail success.

Loan Eligibility Prediction using Gradient Boosting Classifier

Accurate loan eligibility prediction with machine learning, applying SMOTE, data processing, and Random Forest for fair and efficient credit decisions.

Learn to Build a Polynomial Regression Model from Scratch

Learn how to implement polynomial regression to capture complex patterns in data. Discover applications in finance, healthcare, and forecasting with detailed insights and methods.

Machine Learning Deep Learning

Vegetable classification with Parallel CNN model

This tutorial on Vegetable Classification using Machine Learing, guides you through automating the sorting process, improving quality control, and enhancing efficiency in agriculture and food industries.

Insurance Pricing Forecast Using XGBoost Regressor

This project builds an XGBoost Regressor to predict healthcare costs, ensuring insurance profitability. We'll compare it with a linear regression baseline and learn to communicate results effectively to non-technical stakeholders.

Linear Regression Modeling for Soccer Player Performance Prediction in the EPL

This project shows how analytics and AI increase profit and reduce risk in player selection by using linear regression to predict performance for British Premier League football stars.