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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Mentorness\n\nThis repository contains my mentorness internship codes and project resources.\n\n\u003cimg src = \"https://github.com/madhurimarawat/Mentorness/assets/105432776/14d06213-8c44-4c10-a6fb-ffefaca3de2e\" title = \"Internship Description\" alt = \"Internship Description\"\u003e\n\n\n## About Python Programming\n\n--\u003e Python is a high-level, general-purpose, and very popular programming language.\u003cbr\u003e\u003cbr\u003e\n--\u003e Python programming language (latest Python 3) is being used in web development, Machine Learning applications, along with all cutting-edge technology in Software Industry.\u003cbr\u003e\u003cbr\u003e\n--\u003e Python is available across widely used platforms like Windows, Linux, and macOS.\u003cbr\u003e\u003cbr\u003e\n--\u003e The biggest strength of Python is huge collection of standard library.\u003cbr\u003e\n\n---\n## Mode of Execution Used  \u003cimg src=\"https://colab.research.google.com/img/colab_favicon_256px.png\" title=\"Google Colab\" alt=\"Google Colab\" width=\"40\" height=\"40\"\u003e\n\n--\u003e 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.\u003cbr\u003e\u003cbr\u003e\n--\u003e Visit colab at:\u0026nbsp; \u003ca href=\"https://colab.research.google.com/\"\u003e \u003cimg src=\"https://colab.research.google.com/img/colab_favicon_256px.png\" title=\"Google Colab\" alt=\"Google Colab\" width=\"40\" height=\"40\"\u003e\u003c/a\u003e\u003cbr\u003e\u003cbr\u003e\n--\u003e Create account using google account.\u003cbr\u003e\u003cbr\u003e\n--\u003e Once account creation is done, we can directly start coding in colab.\u003cbr\u003e\u003cbr\u003e\n--\u003e It supports Python and R.\u003cbr\u003e\u003cbr\u003e\n--\u003e Files are directly saved in Google Drive.\u003cbr\u003e\u003cbr\u003e\n--\u003e To install python library this command is used-\n```\npip install library_name \n```\n---\n\n## About Projects\n\n\u003cp\u003eComplete Description about the project and resources used.\u003c/p\u003e\n\n## **1. Article Writing**\n\n- My article delves into the world of **Hyperparameter Tuning**.\u003cbr\u003e\u003cbr\u003e\n- It offers a clear explanation of this crucial process in machine learning, detailing how fine-tuning these parameters can significantly boost model performance.\u003cbr\u003e\u003cbr\u003e\n- I've covered various techniques, providing practical insights and examples to help readers understand and implement them effectively.\n\n---\n\n## **2. Customer Churn Prediction**\n\n- In this project I made a streamlit website in which you can apply multiple supervised learning algorithm on Customer churn dataset.\u003cbr\u003e\u003cbr\u003e\n- A multipage streamlit application is made which shows all stages of ml pipeline.\u003cbr\u003e\u003cbr\u003e\n- I also did Data Visualization to show the working of this algorithms on the dataset.\u003cbr\u003e\u003cbr\u003e\n- I have deployed this website using streamlit.\u003cbr\u003e\u003cbr\u003e\n- Visit Website from : \u003ca href=\"https://customer-churn-prediction-ml-pipeline.streamlit.app/\"\u003eCustomer Churn Prediction\u003c/a\u003e\n\n---\n\n## **3. World Cup 2023 Analysis**\n\n- Data Visualization is the presentation of data in pictorial format.\u003cbr\u003e\u003cbr\u003e\n- Target was to see the performance analysis and variations using data visualization.\u003cbr\u003e\u003cbr\u003e\n- In this project visualization of CSV file containing data of players is done in python.\u003cbr\u003e\u003cbr\u003e\n- Data visualization is done to analyze performance of team and players.\u003cbr\u003e\u003cbr\u003e\n- Patterns found in the analysis are listed.\n\n---\n\n## Libraries Used\n\n\u003cp\u003eShort Description about all libraries used in Project.\u003c/p\u003e\n\u003cul\u003e\n  \u003cli\u003ePandas (Panel Data/ Python Data Analysis) - This library is mostly used for analyzing,\ncleaning, exploring, and manipulating data.\u003c/li\u003e\n  \u003cli\u003eMatplotlib - It is a data visualization and graphical plotting library.\u003c/li\u003e\n\u003cli\u003eSeaborn - It is an extension of Matplotlib library used to create more attractive and\ninformative statistical graphics.\u003c/li\u003e\n  \u003cli\u003eStreamlit - It is a Python library that makes it easy to create and share web apps for machine learning and data science projects.\u003c/li\u003e\n\u003c/ul\u003e\n\n---\n\n## Thanks for Visiting 😄\n\n- Drop a 🌟 if you find this repository useful.\u003cbr\u003e\u003cbr\u003e\n- If you have any doubts or suggestions, feel free to reach me.\u003cbr\u003e\u003cbr\u003e\n📫 How to reach me:  \u0026nbsp; [![Linkedin Badge](https://img.shields.io/badge/-madhurima-blue?style=flat\u0026logo=Linkedin\u0026logoColor=white)](https://www.linkedin.com/in/madhurima-rawat/) \u0026nbsp; \u0026nbsp;\n\u003ca href =\"mailto:rawatmadhurima4@gmail.com\"\u003e\u003cimg src=\"https://github.com/madhurimarawat/Machine-Learning-Using-Python/assets/105432776/b6a0873a-e961-42c0-8fbf-ab65828c961a\" height=35 width=30 title=\"Mail Illustration\" alt=\"Mail Illustration📫\" \u003e \u003c/a\u003e\u003cbr\u003e\u003cbr\u003e\n- **Contribute and Discuss:** Feel free to open \u003ca href= \"https://github.com/madhurimarawat/Mentorness/issues\"\u003eissues 🐛\u003c/a\u003e, submit \u003ca href = \"https://github.com/madhurimarawat/Mentorness/pulls\"\u003epull requests 🛠️\u003c/a\u003e, or start \u003ca href = \"https://github.com/madhurimarawat/Mentorness/discussions\"\u003ediscussions 💬\u003c/a\u003e to help improve this repository!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmadhurimarawat%2Fmentorness","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmadhurimarawat%2Fmentorness","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmadhurimarawat%2Fmentorness/lists"}