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SoomroBilal / repository
Welcome to the repository for my final capstone project for the IBM Professional Data Science Certification. This repository contains a collection of Jupyter notebooks showcasing various data science skills and techniques I have acquired during the certification course.
This repository contains the final capstone project for the IBM Professional Data Science Certification. The project is a culmination of the skills and knowledge I have gained throughout the course. The notebooks cover various aspects of data science, including data cleaning, exploratory data analysis, data visualization, machine learning, and more.
Selected from shared topics, language and repository description—not editorial ratings.
Sadia-Khan13 /
Welcome to the Data Cleaning project! This repository is dedicated to showcasing best practices and techniques for cleaning data using Pandas within Jupyter Notebook
Sadia-Khan13 /
Welcome to the Data preprocessing Repository! This repository is dedicated to showcase the comprehensive resources and implementations related to Data Preprocessing using Python and Jupyter Notebook.
jicsjitu /
Welcome to the Financial Analytics Project repository! This project aims to provide a comprehensive analysis of financial data using Python. It includes a CSV file with financial records and a Jupyter Notebook that performs data cleaning, exploratory data analysis, and visualization to uncover insights and trends.
code-griffins /
Explore impactful data science work. Dive into data analysis, machine learning models, and visualizations. Jupyter notebooks detail the process. Welcome to Data Science
priteshmishra739 /
Welcome to the Sales Analysis project! Explore comprehensive sales data analysis using Python and Jupyter Notebook. Gain insights into monthly sales, city-wise performance, and optimal advertisement timing. Discover key patterns through visualizations and detailed documentation.
YuvarajSirra /
This repository analyzes customer data through Exploratory Data Analysis (EDA), a Lookalike Model, and Customer Segmentation using clustering techniques. Key deliverables include Jupyter Notebooks for each task and reports summarizing insights. Clone the repo and install required libraries to get started. Contributions are welcome!