Hands-on Machine Learning - Cryptocurrency Trading [Python]

Name: Hands-on Machine Learning - Cryptocurrency Trading [Python]
Rating: 4.4 (62 reviews)

Learn how to use Machine Learning and Intermarket Analysis to trade Crypto

Created byGenbox Trading

Last updated 5/2022

English

English [Auto],

What you'll learn

How to apply Rule Induction Algorithms in Python
How to perform intermarket analysis
How to download historical data from Python
How to validate Machine Learning Models

Course content

1 section • 8 lectures • 49m total length

Introduction0:47
Learn to build hands-on trading systems for cryptocurrency using market analysis and machine learning. This entry-level course requires only basic Python knowledge and is designed for amateurs and professionals.
Concepts4:36
Learn inter market analysis to gain insights from correlated assets such as Bitcoin and Ethereum and from indices like Nasdaq 100; build data pipelines, model, and apply clipper-based trading rules.
Data Acquisition7:17
Import and configure data libraries in Google Colab, install yfinance, download historical Bitcoin, Etherium, and Nasdaq 100 data, and plot close prices to explore correlations.
Technical Analysis Indicators13:13
Create and apply technical analysis indicators with pandas, including rsi, moving averages, and williams percent range, using btc/usd, eth, and nasdaq data, and explore data length and cross-asset correlations.
Biased Data Labelling4:20
Label cryptocurrency trading data by defining bullish and bearish outcomes from open and next-day prices. Apply thresholds and address costs and class imbalance to emphasize the minority class for learning.
Rule Induction with RIPPER5:23
Induce rules with RIPPER to predict cryptocurrency market movements using indicator features, splitting data 70/30 for training and testing, and backtesting the resulting rule set.
Backtesting our Model7:59
Backtest a cryptocurrency trading model by generating test predictions, evaluating accuracy, and plotting the equity curve with base capital while using Williams and Bitcoin indicators.
Reading and Trading our Rules6:19
Translate cryptocurrency trading rules by interpreting indicators like RSI and Williams ten, then trade manually or with python using platforms such as Binance and TradeStation.

Requirements

None

Description

In this course you are going to learn how to take your trading to the next level applying different techniques to analyze the market and create powerful trading signals.

This course is mainly divided into two concepts.

Intermarket Analysis: Since Cryptocurrencies don’t have much historical data, we need to gain insights by being creative.

In order to analyze one security, we are going to use data from that security and many others.

Let’s say we are analyzing Bitcoin, in that case we will use Bitcoin data, and also Ethereum and even stock indexes.

Once we have mastered that concept, it’s time to roll up our sleeves and start coding.

Using Python you are going to learn how to download historical data and create indicators to gain insights from that data.

Then you are going to learn how to create biased labels to optimize what our algorithm needs to learn.

Finally, once we have everything prepared, we are going to use RIPPER (Repeated Incremental Pruning to Produce Error Reduction) as our rule induction algorithm in order to create readable rules that will result in powerful trading systems.

At the end of this course, you will have your own trading system generator.

Who this course is for:

Traders and coders who want to learn new techniques to analyze the cryptocurrency markets