As a Machine learning expert when you are learning this skills you always wanted to develop a complete Machine learning application where you would have a UI to feed in some inputs and the Machine learning model to predict on those values.
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There are many different ways two can build machine learning app but you'll have to take care about front end and back end.
The front-end is developed in React and would include a single page with a form to submit the input values
The back-end is developed in Flask which exposes prediction endpoints to predict using a trained classifier and send the result back to the front-end for easy consumption
You can build simple app easy to use template in React and Flask
You can also build a machine learning python CLI tool that analyzed a database of 4 types of answers (low, medium, hot, extremely hot). Then, python would analyze the next question and attempt to answer it based on the previous answers. If it was wrong, it would learn from its mistakes. Since there are multiple different answers, maybe try lineReg.coef_? I think you would need to use a linear regression algorithm to accomplish this request, but let me know.
Basic Steps in Machine Learning to create app
Create your Machine Learning model
Choose Front end
Run your App
Streamlit app for your data science project and deploying it on Heroku
Step 1: Build your project
Build a streaming service that captures tweets related to a particular hashtag in real-time and then does sentiment analysis of those tweets.
Python library used of is tweepy: Tweepy is a python wrapper around the Twitter API, which helps you mine twitter data.
Step 2: Design a web app using Streamlit
Step 3: Deploy on Heroku
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