CODSOFT Explore my Data Science Internship Portfolio, featuring projects completed during my time at Codsoft. These projects highlight my proficiency in data analysis, machine learning, and creative problem-solving. Check out the summaries below for an overview." PROJECTS:

1. Titanic Survival Detection Project: This project aims to analyze the Titanic dataset to forecast passenger survival. It encompasses tasks such as data preprocessing, exploring the data, and constructing a machine learning model to estimate survival probabilities.

2. Iris Flower Classification: This project tackles the classic machine learning problem of classifying iris flowers using the Iris dataset. It entails categorizing iris flowers into different species based on measurements of their sepals and petals.

3.Sales Prediction Python: This project delves into the role of Data Scientists in leveraging Python's machine learning capabilities to analyze and interpret data for informed decision-making on advertising costs. By optimizing predictions, businesses can refine their advertising strategies and maximize sales potential. Join us on the journey of mastering sales prediction techniques through machine learning in Python.

4. Credit Card Fraud Detection: It covers preprocessing and normalization of transaction data, addressing class imbalance, and splitting the dataset for training and testing. The model employs classification algorithms like logistic regression or random forests to classify transactions accurately. Evaluation metrics such as precision, recall, and F1-score are used to assess the model's performance, along with techniques like oversampling or undersampling for improved results. Explore and implement effective fraud detection techniques with this repository.