A data analysis report on ligand crystallography

Data Analysis project analyzing the characteristics of credit card borrowers. After the analysis, a classification model is built.

The project is based upon the kaggle dataset of Heart Disease UCI. The final model is generated by Random Forest Classifier algorithm, which gave an accuracy of 88.52% over the test dataset that is generated randomly choosing of 20% from the main dataset.

Determine the most significant protective and risk factors when it comes to identifying the prevalence of cardiovascular disease in a patient

Data engineering and machine learning operations

EDISS Winter School 2024 Hackathon

This project is a machine learning model that predicts the next event type in the game Egg, Inc. based on historical event data.

This is the second task in my internship with Codsoft about movie ratings prediction

Different ML Algorithms both in scripts & Jupyter Notebooks

This repository contains two sample implementations of the traditional Computer Vision task, Digit Recognizer from Kaggle. The URL of the dataset and relevant information can be found here: https://www.kaggle.com/c/digit-recognizer

Predicting if a system is vulnerable for malware. Analysis on different models.

Using supervised machine learning models to assess credit risk using Python

End-to-end implementation and deployment of Machine Learning Diabetes Predictor web application created using python, flask, gunicorn, scikit-Learn, etc., and deployed on the Heroku web application platform.

This is my version of analysis of Zomato Bangalore Dataset

This is a beginner project that uses Machine Learning Algorithms to predict the prices of houses in the California region, also Flask is used for deployment of the model thus created.

Use data visualization, hypothesis testing and machine learning methods to analyze StackOverflow developers survey data.

Parkinson’s disease classification using speech signal features; comparison of various multiclass classification algorithms

AI/ML Project on Breast Cancer Prediction (Python) using ML- Algorithms : Logisitic Regression, Decision Tree Classifier, Random Forest Classifier, Support Vector Machine Classifier, Gaussian Naive Bayes Algorithm Model, Stochastic gradient descent Classifier, Gradient Boosting Classifier . And also perform a comparative analysis of all the seve…