Hands-on Machine Learning for Stock Trading [Python]
Unleash the power of Neural Networks for Trading
Note: 0/5 (0 notes) 382 students
Instructor(s): Genbox Trading
Last update: None
What you’ll learn
- How to create a Neural Network with Python
- How to prepare data for Time Series Analysis
- How to evaluate Machine Learning models
- How to perform a reliable backtest with Python
- Basic knowledge of Python
Enter the world of Neural Networks and Financial Forecasting with this free course.
Can you forecast the returns of your favorite stock using Machine Learning?
Artificial Intelligence is certainly changing the world:
From the way we get our content, autonomous driving, medical advances to art creation.
Financial Machine Learning is one of the industries with a bigger impact on these technologies, from Roboadvisors to Algorithmic Trading.
Most recommendations made by firms are based on Artificial Intelligence nowadays, rendering most conventional analysts useless.
The same happens for traders, not many years ago trading was done manually, currently a huge share of the market is being traded by AI.
These advances have changed the game, gaining insight with edges the human eye can’t see anymore.
While the biggest financial institutions have been trading using Artificial Intelligence for years, most retail traders don’t know how to use nor benefit from them, we are here to change that.
Roll up your sleeves with this hands-on project where you are going to learn by doing and interacting with code, completely from scratch.
In this course you are going to learn how to:
Download Historical Data from your code, automatically.
Prepare your data with the most suitable indicators.
How to label and prepare data to feed our model.
Prepare a Neural Network.
Backtest your ML Model.
Create accurate stock forecasts.
We hope you enjoy this course.
Who this course is for
- traders and coders who wants to use Machine Learning
- Getting historical data
- Creating technical analysis indicators
- Labelling our data
- Training our Neural Network
- Backtesting our Model
- Forecasting today returns
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