This repository contains Machine learning and deep learning project
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Credit Card Fraud Detection : Credit-card fraud is when someone uses our credit card or credit account to make a purchase we didn't authorize. Credit-card companies should take necessary actions to prevent fraudulent credit-card transactions. In this project, we develop an ML model to detect credit-card fraud.
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Predict Customer Churn with Python : Customer churn (also known as customer attrition) is the loss of clients or customers. It is most commonly expressed as the percentage of service subscribers who discontinue their subscriptions within a given time period. In this project, we will build a machine learning model to predict customer churn.
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Rainfall in Australia Rainfall is a critical factor influencing various aspects of human life. To better understand and predict rainfall patterns, I developed a binary classification model using Logistic Regression. This model aims to forecast whether it will rain in Australia on a specific day. I employed the "Rain in Australia" dataset and the powerful Scikit-learn library in Python to train and evaluate the model.
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Sentiment Analysis with Python : Sentiment analysis, also known as opinion mining, is a technique in natural language processing (NLP) that aims to identify and interpret the emotional tone within a piece of text. It’s widely used by organizations to gauge public opinion or customer feedback on products, services, or ideas. By applying data mining, machine learning, and artificial intelligence (AI), sentiment analysis systems can automatically analyze large volumes of unstructured text data.