Here, I've curated a collection of small yet fascinating machine learning projects. These projects showcase my strong foundational knowledge and skills in the exciting world of ML. Each project explores different facets of machine learning, allowing me to demonstrate my proficiency in various techniques and algorithms.

NOTE: All the datasets can be found on Kaggle.

Project Descriptions

• Diabetic Patients Classification: This project focuses on predicting whether a patient has diabetes or not based on several medical attributes. By applying classification algorithms, I aim to build a model that can assist in early detection and intervention.
• Gender Prediction based on Voice: Through this project, I delve into the realm of speech analysis and gender recognition. Using voice features and machine learning algorithms, I've developed a model capable of predicting the gender of a speaker based on their voice characteristics.
• House Price Prediction: Real estate enthusiasts will find this project intriguing. Here, I've employed regression techniques to predict the prices of houses based on various features such as location, size, and amenities. This model can assist both buyers and sellers in making informed decisions.
• Breast Cancer Prediction: Early detection of breast cancer is crucial for effective treatment. In this project, I've built a classification model that analyzes breast cancer data to predict whether a tumor is benign or malignant, aiding in the diagnosis process. I have also performed hyperparameter tuning for better results.
• Income Prediction Project: By leveraging machine learning algorithms and socio-economic attributes, this project aims to predict the income level of individuals. It has applications in various fields, such as market research, loan assessment, and demographic analysis.
• Petrol Consumption Prediction: Fuel consumption is a significant concern in today's world. Using regression techniques, I've developed a model that predicts petrol consumption based on factors like distance traveled, vehicle specifications, and driving conditions. This can help optimize fuel efficiency and reduce carbon emissions.
• Titanic Survivor Prediction: Inspired by the infamous Titanic disaster, this project focuses on predicting the survival chances of passengers based on various attributes. By applying classification algorithms to historical data, I aim to uncover patterns that influence survival rates.
• Wine Quality Classification: Wine connoisseurs and enthusiasts will find this project intriguing. Here, I explore the classification of wine quality using machine learning algorithms. By analyzing sensory and chemical attributes, the model predicts the quality of a given wine sample.

Feel free to explore these projects and delve into the code that I've provided. Each project highlights my ability to handle different ML tasks and showcases my passion for leveraging data to gain insights and make predictions.