Skip to content

Latest commit

 

History

History
50 lines (38 loc) · 2.5 KB

README.md

File metadata and controls

50 lines (38 loc) · 2.5 KB

CodSoft Internship Projects

This repository contains the projects I completed during my internship at CodSoft. These projects are focused on Data Science and showcase my skills in data analysis, machine learning, and Python development.

Projects Overview

1. Titanic Survival Prediction

  • Objective: Predict the survival of passengers aboard the Titanic using machine learning techniques.
  • Tools Used: Python, Pandas, NumPy, Scikit-learn
  • Algorithms: Logistic Regression, Decision Trees, Random Forest
  • Summary: This project applies data preprocessing, feature engineering, and model evaluation to accurately predict passenger survival. I experimented with different algorithms to compare their performance.

View Project

2. Movie Rating Prediction

  • Objective: Predict movie ratings based on user behavior and preferences.
  • Tools Used: Python, Pandas, NumPy, Scikit-learn, Surprise
  • Algorithms: Collaborative Filtering, Matrix Factorization
  • Summary: A recommendation system project that leverages collaborative filtering techniques to predict user ratings of movies. I worked on improving the accuracy of the model by tuning hyperparameters.

View Project

3. Credit Card Fraud Detection

  • Objective: Identify fraudulent credit card transactions from a dataset of transactions.
  • Tools Used: Python, Pandas, NumPy, Scikit-learn
  • Algorithms: Logistic Regression, Decision Trees, Random Forest, Gradient Boosting
  • Summary: This project focuses on identifying fraudulent transactions using a variety of classification techniques. The dataset is highly imbalanced, and techniques such as SMOTE were applied to address the imbalance.

View Project

Getting Started

  1. Clone the repository: 
    git clone https://github.com/shashmitha46/-CODSOFT-.git

2.Navigate to the project folder:

cd project-folder

3.Install the required dependencies:

pip install -r requirements.txt

Tools & Technologies

  • Programming Language: Python
  • Libraries: Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Surprise
  • Development Environment: Jupyter Notebooks

Thank you for visiting my repository! 😊😊😊