Given developer's data, predicts the salary using Boston House Price dataset with python & jupyter-notebook IDE, a web based Machine Leaning App.

This is a Python-based news classifier that uses machine learning to classify news articles into different categories such as business, sports, crime, and science. The model is built using the natural language processing (NLP) library, NLTK, and the scikit-learn machine learning library.

Regression model to predict flight fares

This deals with EDA and building various ML models using sklearn: KNeighborsRegressor DecisionTreeRegressor RandomForestRegressor,AdaBoostRegressor LinearRegression, Ridge,Lasso, etc and HP using randomCV and deploy the same in localhost via flask

This end-to-end machine learning project is focused on predicting medical insurance price using regression.

Loan Default Detector App built with XGBoost, FastApi, Docker and Streamlit

Developed a machine learning model using the Cleveland Heart Disease dataset to accurately predict heart disease presence in individuals based on 14 medical attributes. Conducted comprehensive data exploration, visualization, model selection, training, hyperparameter tuning, and evaluation. Identified crucial features to aid diagnosis and treatment

This machine learning project aims to recommend the most suitable crop to grow based on various soil and environmental factors. The model takes into account the following input data:

Regression model to predict IPL scores

Welcome to this repository! This project uses data science and machine learning to predict retail product sales prices. It includes a robust data preprocessing pipeline, handles outliers, and features an ensemble model. With real-time predictions through a user-friendly Flask app and API, it's a game-changer for businesses seeking accurate sales.

Comparing the Logistic Regression Model and Random Forest Classifier

Repository used for twitter impression models

"Introduction to Machine Learning" course 2016

My Coursera assignments

ML Backend for TechBhet.com that does text classification on FB Group posts.

Practice from the book Hands On Machine Learning with sklearn and TensorFlow

Code for ML presentation.

Python library practice (2017)

This is a Kaggle competition sponsored by Memorial Sloan Kettering Cancer Center. This competition is the first step in personalized medicine to determine oncogenicity of a tumor. Algorithm using sparse words to predict gene mutations effect on protein function.

🏎️ Vehicle Detection Project using OpenCV and scikit-learn for the Self-Driving Car Nanodegree at Udacity