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janhabi28 / repository
📌 This project is a Movie Recommender System built using Machine Learning algorithms in a Jupyter Notebook environment, powered by Anaconda. It helps users discover movies they might enjoy based on user preferences, ratings, and content features.
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📌 This project is a Movie Recommender System built using Machine Learning algorithms in a Jupyter Notebook environment, powered by Anaconda. It helps users discover movies they might enjoy based on user preferences, ratings, and content features.
Selected from shared topics, language and repository description—not editorial ratings.
itprodirect /
📌 Model Context Protocol 102 (MCP-102) - API Tutorial with Jupyter Notebook A beginner-friendly tutorial on using MCP APIs inside a Jupyter Notebook. This repository covers virtual environment setup, API requests with Python, and best practices for structuring projects using Git and GitHub.
52/100 health9637231757 /
# 📊 Data Analysis Projects Repository ## 📌 Overview This repository contains multiple **end-to-end Data Analysis projects** developed using **Python** and **Jupyter Notebook (Google Colab)**. Each project focuses on real-world datasets and demonstrates the complete data analysis workflow including **data cleaning, exploratory data analysis (EDA)
42/100 healthJeniffer-sys /
📌 Project Overview This project analyzes global sales performance using data cleaning, transformation, and visualization techniques. The Jupyter Notebook (Final_Project_Global_Sales_Performance.ipynb) demonstrates step-by-step analysis of sales data to uncover trends, insights, and performance metrics across regions, products, and time periods.
vikashgupta630 /
🏏 IPL Data Analysis Project 📌 Project Overview This project focuses on analyzing Indian Premier League (IPL) datasets to extract meaningful insights about teams, players, and match performances. Using Python, Pandas, Matplotlib/Seaborn, and Jupyter Notebook, the project highlights various statistical patterns and trends from IPL history.
34/100 healthReshmakhaan /
🧠 Project Title: Exploratory Data Analysis on Diwali Sales Dataset 📌 Objective: The main goal of this project is to perform Exploratory Data Analysis (EDA) on the Diwali Sales Dataset to uncover customer purchasing behavior🛠 Tools & Technologies Used: Python (Pandas, NumPy, Matplotlib, Seaborn) Jupyter Notebook a
27/100 healthnaveenkumar279 /
🛍️ Diwali Sales Data Analysis 📌 -This project involves an in-depth Exploratory Data Analysis (EDA) on Diwali Sales Dataset using Python (Pandas, Matplotlib, Seaborn) in Jupyter Notebook. The objective is to derive valuable business insights from customer purchasing behavior during the Diwali festival.
27/100 health