Popular GitHub Repositories for Logistics Regression

Stock Market Price Prediction: Used machine learning algorithms such as Linear Regression, Logistics Regression, Naive Bayes, K Nearest Neighbor, Support Vector Machine, Decision Tree, and Random Forest to identify which algorithm gives better results. Used Neural Networks such as Auto ARIMA, Prophet(Time-Series), and LSTM(Long Term-Short Memory) then compare make Inferences about the model.

Create, deploy and interact with a Machine Learning model in real time. Project involves training a Logistics Regression model for a binary classification task and deploying the trained model in a webserver to obtain real-time predictions via rest API using a simple web page