Machine Learning Projects
Welcome to my repository showcasing various machine learning projects! In this repository, you'll find a collection of projects where I've applied machine learning algorithms to analyze datasets and solve real-world problems.
Automobile Dataset Analysis Description: Explored and analyzed a dataset related to automobiles using Python and various machine learning techniques to predict certain outcomes or trends.
Breast Cancer Dataset Analysis Description: Conducted an in-depth analysis of a breast cancer dataset using machine learning algorithms to classify tumors as benign or malignant, contributing to the understanding and diagnosis of breast cancer.
Digits Dataset Neural Network Description: Implemented a neural network model to classify handwritten digits using the famous MNIST dataset, achieving accurate recognition through deep learning techniques.
Linear Regression & IRIS Practice Description: Applied linear regression techniques on the IRIS dataset for prediction and classification tasks, gaining insights into the relationships between variables and species classification.
Titanic Survival Prediction with Random Forest Description: Utilized the Random Forest algorithm to predict survival outcomes of passengers aboard the Titanic, providing insights into factors influencing survival rates.
Wine Recognition with Six Algorithms Description: Employed six different machine learning algorithms to recognize wine types based on various features, comparing their performance and accuracy for classification tasks.
XG Boost, KNN, RF Digit Recognizer Description: Developed a digit recognizer system using XG Boost, K-Nearest Neighbors (KNN), and Random Forest algorithms, achieving high accuracy in recognizing handwritten digits. Usage
Contact
If you are interested in connecting with me for inquiries or collaboration opportunities, feel free to reach out through the following channels:
Email: aruvibalamurugan@gmail.com LinkedIn: Aruvi B. GitHub: Aruvi B Looking forward to connecting with you!
Happy exploring!