Performing analyses on New York City Airbnb and developing business intelligence for both the hosts and the guests

CharityML is a fictitious charity organization located in the heart of Silicon Valley that was established to provide financial support for people eager to learn machine learning. After nearly 32,000 letters were sent to people in the community, CharityML determined that every donation they received came from someone that was making more than $5…

In this project, we analyze and compare the performance of various machine learning algorithms (Linear Regression, Decision Tree, AdaBoost, XGBoost, Gradient Boosting and k- Nearest Neighbors) when used to predict hard drive failures using Backblaze data in the year 2018.

CART, K-Means, Apriori, Adaboost, RFE; models using Anti-cancer peptides vs Human proteins

This project explores the working of various Boosting algorithms and analyzes the results across different algorithms. Algorithms Used are: Random Forest, Ada Boost, Gradient Boost and XG Boost

First project Of machine learning Nanodegree (Supervised Learning)