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.
- 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.
- 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.
- 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.
- Clone the repository:
git clone https://github.com/shashmitha46/-CODSOFT-.git
2.Navigate to the project folder:
cd project-folder3.Install the required dependencies:
pip install -r requirements.txt- Programming Language: Python
- Libraries: Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Surprise
- Development Environment: Jupyter Notebooks
Thank you for visiting my repository! 😊