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https://github.com/madhurimarawat/mentorness
This repository contains my mentorness internship codes and project resources.
https://github.com/madhurimarawat/mentorness
article-writing customer-churn-prediction customer-churn-prediction-with-machine-learning data-analysis-python data-science deployed detailed-analysis hyperparameter-tuning internship-project machine-learning machine-learning-algorithms presentation-materials presentation-slides projects projects-repository python streamlit-application streamlit-sharing video-presentation world-cup-2023
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This repository contains my mentorness internship codes and project resources.
- Host: GitHub
- URL: https://github.com/madhurimarawat/mentorness
- Owner: madhurimarawat
- License: apache-2.0
- Created: 2024-03-21T06:01:16.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-06-30T07:12:50.000Z (5 months ago)
- Last Synced: 2024-07-01T14:08:25.022Z (5 months ago)
- Topics: article-writing, customer-churn-prediction, customer-churn-prediction-with-machine-learning, data-analysis-python, data-science, deployed, detailed-analysis, hyperparameter-tuning, internship-project, machine-learning, machine-learning-algorithms, presentation-materials, presentation-slides, projects, projects-repository, python, streamlit-application, streamlit-sharing, video-presentation, world-cup-2023
- Language: Jupyter Notebook
- Homepage: https://customer-churn-prediction-ml-pipeline.streamlit.app/
- Size: 7.21 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Mentorness
This repository contains my mentorness internship codes and project resources.
## About Python Programming
--> Python is a high-level, general-purpose, and very popular programming language.
--> Python programming language (latest Python 3) is being used in web development, Machine Learning applications, along with all cutting-edge technology in Software Industry.
--> Python is available across widely used platforms like Windows, Linux, and macOS.
--> The biggest strength of Python is huge collection of standard library.
---
## Mode of Execution Used 
--> Colaboratory, or “Colab” for short, is a product from Google Research which allows anybody to write and execute python code in Jupyter notebook through the browser.
--> Visit colab at:
--> Create account using google account.
--> Once account creation is done, we can directly start coding in colab.
--> It supports Python and R.
--> Files are directly saved in Google Drive.
--> To install python library this command is used-
```
pip install library_name
```
---
## About Projects
Complete Description about the project and resources used.
## **1. Article Writing**
- My article delves into the world of **Hyperparameter Tuning**.
- It offers a clear explanation of this crucial process in machine learning, detailing how fine-tuning these parameters can significantly boost model performance.
- I've covered various techniques, providing practical insights and examples to help readers understand and implement them effectively.
---
## **2. Customer Churn Prediction**
- In this project I made a streamlit website in which you can apply multiple supervised learning algorithm on Customer churn dataset.
- A multipage streamlit application is made which shows all stages of ml pipeline.
- I also did Data Visualization to show the working of this algorithms on the dataset.
- I have deployed this website using streamlit.
- Visit Website from : Customer Churn Prediction
---
## **3. World Cup 2023 Analysis**
- Data Visualization is the presentation of data in pictorial format.
- Target was to see the performance analysis and variations using data visualization.
- In this project visualization of CSV file containing data of players is done in python.
- Data visualization is done to analyze performance of team and players.
- Patterns found in the analysis are listed.
---
## Libraries Used
Short Description about all libraries used in Project.
- Pandas (Panel Data/ Python Data Analysis) - This library is mostly used for analyzing,
cleaning, exploring, and manipulating data. - Matplotlib - It is a data visualization and graphical plotting library.
- Seaborn - It is an extension of Matplotlib library used to create more attractive and
informative statistical graphics. - Streamlit - It is a Python library that makes it easy to create and share web apps for machine learning and data science projects.
---
## Thanks for Visiting 😄
- Drop a 🌟 if you find this repository useful.
- If you have any doubts or suggestions, feel free to reach me.
📫 How to reach me: [](https://www.linkedin.com/in/madhurima-rawat/)
- **Contribute and Discuss:** Feel free to open issues 🐛, submit pull requests 🛠️, or start discussions 💬 to help improve this repository!