Hands-on Machine Learning for Stock Trading [Python]

Name: Hands-on Machine Learning for Stock Trading [Python]
Rating: 4.3 (214 reviews)

Unleash the power of Neural Networks for Trading

Created byGenbox Trading

Last updated 5/2022

English

English [Auto],

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

Course content

1 section • 8 lectures • 46m total length

Introduction1:19
Build and validate a machine learning model for stock trading with python, focusing on time series analysis and forecasting.
Model5:12
acquire historical data from Yahoo Finance and compute technical analysis indicators to train a supervised neural network with binary up or down labels, backtest its performance, and forecast stock movements.
Getting historical data10:44
Learn to fetch historic stock data in Google Colab using the Yahoo! Finance library, download Apple (AAPL) prices from 2010 onward, and plot the closing price for quick validation.
Creating technical analysis indicators7:16
Import a technical analysis library to create RSI and CCI indicators on closing, high, and low prices in a dataframe, account for empty values, and plot the indicators together.
Labelling our data5:23
Label trading data by creating a new label column from next day open and close, signaling buy bias when close exceeds open. Use numpy and indicators to classify outcomes.
Training our Neural Network10:37
Train a neural network using an MLP classifier on indicator features from Yahoo Finance. Split data into train and test sets, and evaluate classification reports for buying signals.
Backtesting our Model2:48
Backtest the stock trading model by generating timeframe predictions with numpy, building a dataframe strategy, and measuring next-day buy and one-day sell returns with plotted results.
Forecasting today returns2:57
Forecast today returns by building technical analysis indicators and preparing labels for a neural network to predict stock moves, including Dow and Tesla, with retraining to improve accuracy.

Requirements

Basic knowledge of Python

Description

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.
Evaluate models.
Backtest your ML Model.
Create accurate stock forecasts.

We hope you enjoy this course.

Genbox Trading

Who this course is for:

traders and coders who wants to use Machine Learning