Data Science Internship Tasks at Coder Caves

Overview

This repository documents the tasks and projects completed during my data science internship at Coder Caves. Throughout the internship, I worked on a variety of data-driven projects and tasks, gaining hands-on experience in the field of data science.

Key Highlights

• Exploratory Data Analysis (EDA): Explored and analyzed diverse datasets to extract valuable insights.
• Machine Learning: Implemented machine learning algorithms for predictive modeling and classification tasks.
• Data Visualization: Created informative visualizations using tools like Matplotlib and Seaborn.
• Statistical Analysis: Conducted statistical tests and hypothesis testing to draw meaningful conclusions.
• Data Cleaning and Preprocessing: Worked on data preprocessing techniques to prepare datasets for analysis.
• Documentation: Documented project findings, methodologies, and code for future reference.

Technologies and Tools

• Python
• Google colab
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Statistical Tools (if applicable)

Repository Structure

• Task 1: Exploratory_data_analysis_terrorism
• Task 2: Breast Cancer Prediction
• Task 2: EmailSpamDetection