Stock Market Screening and Analysis: Using Web Scraping, Neural Networks, and Regression Analysis in Investing
Increasing portfolio returns using python Source
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Implementing Logistic Regression for Stock Trading
Most stock trading algorithms that incorporate machine learning are based upon some form of linear regression. There are benefits and drawbacks to this method. Source
I Used Machine Learning To Create A Stock Price Predictor
There are two analyses in a stock price analysis — fundamental analysis and technical analysis. Fundamental analysis is focused on analysis of the company’s future growth based on current business environment and financial performance such ...
Time-Series Forecasting: Predicting Stock Prices Using Facebook’s Prophet Model
In this post, I show you how to predict stock prices using a forecasting model publicly available from the Facebook Data Science team: The Prophet Source
Build a ML Web App for Stock Market Prediction From Daily News With Streamlit and Python
On the web interface, you can simply start from choosing your ML model type, then adjusting hyperparameters of the model and finally selecting your evaluation metrics. Source
Combining Technical Indicators with Deep Learning for Stock Trading
This project is not a deep dive into connecting technical analysis and machine learning, but just a simple framework so that the reader can work upon it and implement their own features. Source
Automating Stock Investing Fundamental Analysis With Python
Explaining Stock Trading Fundamental Analysis Ratios And Retrieving Them Using Python Source
How Does Machine Learning Perform in the Stock Market?
How to Use Vectorized Backtesting to Evaluate ML Models Source
Profitable $tock trading models and Jupyter notebook
Stock trading models can look enticing, testing them against historical data often reveals a less promising reality. And sometimes the output of a model is itself material for a model with curious correlation to actual ...