{"repo":"madhurimarawat/ML-Model-Datasets-Using-Streamlits","free":true,"listed":false,"github":"https://github.com/madhurimarawat/ML-Model-Datasets-Using-Streamlits","clone":"git clone https://github.com/madhurimarawat/ML-Model-Datasets-Using-Streamlits.git","description":"This repository contains my machine learning models implementation code using streamlit in the Python programming language.","language":"Jupyter Notebook","stars":17,"topics":["classifier","data-visualization","decision-tree","diabetes-dataset","digits-dataset","kaggle-datasets","knn","linear-regression","logistic-regression","naive-bayes-algorithm"],"license":"MIT","category":"machine-learning","readme_excerpt":"ML-Model-Datasets-Using-Streamlits This repository contains my machine learning models implementation code using streamlit in the Python programming language. --- Mode of Execution Used   Pycharm -- Visit the official website of pycharm: -- Download according to the platform that will be used like Linux, Macos or Windows. -- Two versions of Pycharm are avilable- 1. Community version -- Community version is open source and we can use it for free without any paid plan. -- We can download this at the end of pycharm website. -- After downloading community version we can directly follow the setup wizard and it will be setup. 2. Professional Version. -- This is available at the top of website, we can directly download from there. -- After downloading professional version, follow the below steps. -- Follow the setup wizard and sign up for the free version (trial version) or else continue with the premium or paid version. Using Pycharm -- First, in pycharm we have the concept of virtual environment. In virtual environment we can install all the required libraries or frameworks. -- Each project has its own virtual environment, so thath we can install requirements like Libraries or Framworks for that project only. -- After this we can create a new file, various file types are available in pycharm like script files, text files and also Jupyter Notebooks. -- After selecting the required file type, we can continue the execution of that file by saving it and using this shortcut shift+","default_branch":null,"files":null,"tree":[],"storefront":"/r/madhurimarawat","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/madhurimarawat/ML-Model-Datasets-Using-Streamlits/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}