Machine Learning in Python for Cryptocurrency Trading

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Tauqeer Khurram

7:32:06

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1. Getting Started

1. Promo Video (Introduction).mp4

03:03

2. Coding Environments

1.1 01 Setting up the Coding Environment - Part 1.pptx

1. 02 Setting up the Coding Environment - 1.mp4

20:13

2.1 02 Setting up the Coding Environment - Part 2.pptx

2. 02 Setting up the Coding Environment - 2.mp4

09:52

3. Python Crash Course

1.1 01 Python Crash Course - Overview.pptx

1. 01 Python Crash Course - Overview.mp4

03:03

2.1 02 Python Comments.pptx

2. 03 Python Comments.mp4

06:53

3.1 03 Python Variables.pptx

3. 03 Python Variables.mp4

10:29

4.1 04 Python Functions and Methods.pptx

4. 04 Python Functions and Methods.mp4

07:24

5.1 05 Data types in Python.pptx

5. 05 Data types in Python.mp4

07:22

6.1 06 Pandas DataFrame.pptx

6. 06 Pandas DataFrame.mp4

03:10

7.1 07 CSV Data Files Format.pptx

7. 07 CSV Data Files Format.mp4

04:02

8.1 08 Python Libraries.pptx

8. 08 Python Libraries.mp4

10:30

4. 04 Machine Learning

1.1 01 Machine Learning - Introduction.pptx

1. 01 Machine Learning - Introduction.mp4

10:04

2.1 02 Machine Learning for Crypto Trading.pptx

2. 02 Machine Learning for Crypto Trading.mp4

02:56

3.1 03 Machine Learning Algorithms 101.pptx

3. 03 Machine Learning Algorithms 101.mp4

03:26

4.1 04 Machine Learning Models 101.pptx

4. 04 Machine Learning Models 101.mp4

02:22

5.1 05 ML Algorithms vs ML Models - The Difference.pptx

5. 05 ML Algorithms vs ML Models - The Difference.mp4

04:57

6.1 06 Regression vs Classification.pptx

6. 06 Regression vs Classification.mp4

05:47

5. 05 Cryptocurrency Data Preprocessing & Analysis

1.1 01 Candlestick OHLC.pptx

1. 01 Candlestick OHLC.mp4

06:33

2.1 02 obtaining crypto data using yfinance.zip

2.2 02 Obtaining Crypto Data Using yFinance.pptx

2.3 Crypto Port.csv

2. 02 Obtaining Crypto data Using yFinance.mp4

23:22

3.1 03 data inspection and visualization.zip

3.2 03 Data Inspection and Visualization.pptx

3.3 Crypto Port.csv

3.4 CryptoClose.csv

3. 03 Data Inspection and visualization.mp4

31:21

4.1 04 Crypto Performance Evaluation.pptx

4.2 04 measuring cryptocurrency performance.zip

4.3 CryptoClose.csv

4. 04 Measuring Cryptocurrency Performance.mp4

35:30

5.1 05 calculating returns from historical data.zip

5.2 05 Calculating Returns from Historical Data.pptx

5.3 CryptoClose.csv

5. 05 Calculating Returns from Historical Data.mp4

21:50

6.1 05 calculating returns from historical data.zip

6.2 05 Calculating Returns from Historical Data.pptx

6.3 CryptoClose.csv

6. 05 Calculating Returns from Historical Data.mp4

21:50

7.1 06 regularization or normalization of data.zip

7.2 06 Regularization or Normalization of Data.pptx

7.3 CryptoClose.csv

7. 06 Regularization or Normalization of Data.mp4

10:40

8.1 07 covariance and correlation.zip

8.2 07 Covariance and Correlation.pptx

8.3 CryptoClose.csv

8. 07 Covariance and Correlation.mp4

13:55

6. 06 Performance Evaluation of Cryptocurrencies

1.1 01 performance evaluation (risk-return).zip

1.2 01 Performance Evaluation (Risk-Return).pptx

1.3 CryptoClose.csv

1. 01 Performance Evaluation (Risk-Return).mp4

16:04

2.1 02 ethusd data download.zip

2.2 02 ETHUSD Data Download.pptx

2.3 ETHUSD.csv

2. 02 ETHUSD Data Download.mp4

06:15

7. 07 Predicting Crypto Prices with Machine Learning

1.1 01 Simple Linear Regression.pptx

1. 01 Simple Linear Regression.mp4

03:08

2.1 02 predicting crypto prices - simple linear regression.zip

2.2 02 Predicting Crypto Prices - Simple Linear Regression.pptx

2.3 ETHUSD.csv

2. 02 Predicting Crypto Prices - Simple Linear Regression.mp4

30:54

3.1 03 Support Vector Machine (SVM).pptx

3. 03 Support Vector Machine (SVM).mp4

16:02

4.1 04 predicting crypto prices - svm.zip

4.2 04 Predicting Crypto Prices - SVM.pptx

4.3 ETHUSD.csv

4. 04 Predicting Crypto Prices - SVM.mp4

27:52

5.1 05 XGBoost.pptx

5. 05 XGBoost.mp4

01:42

6.1 06 predicting crypto prices - xgboost.zip

6.2 06 Predicting Crypto Prices - XGBoost.pptx

6.3 ETHUSD.csv

6. 06 Predicting Crypto Prices - XGBoost.mp4

11:47

8. 08 ML Model Evaluation

1.1 02 Residual Error.pptx

1. 01 Residual Error.mp4

05:47

2.1 03 R Squared Error Intuition.pptx

2. 02 R Squred Error Intuition.mp4

11:17

3.1 03 R Squared Error Implementation.pptx

3.2 03 r squared error.zip

3. 03 R Squared Error Implementation.mp4

03:29

9. 09 ML Model Deployment

1.1 09 ML Model Deployment.pptx

1.2 09 ML Model Deployment.rar

1. 09 ML Model Deployment.mp4

37:15

Description

Learn to predict cryptocurrency future prices using the power of Python Machine Learning (Artificial Intelligence)

What You'll Learn?

Learn to Predict Future Cryptocurrency Prices with ML Python Coding.
Learn to Build Machine Learning Models for Cryptocurrency Price Predictions.
Create a Web App that will Predict Cryptocurrency Future Prices.
Learn to Deploy Machine Learning Models for Cryptocurrency Price Prediction.

Who is this for?

Python Programmers, Data Scientist, Algorithmic Traders, AI Engineers, Computer Programmers, Cryptocurrency junkies and enthusiasts, Machine Learning Engineers who want to learn to predict future cryptocurrency prices.

What You Need to Know?

Very little or no programming language experience required, you will learn everything you need to know

Knowledge of Markup languages such as HTM5 and CSS3 will help.

More details

Description
It is a comprehensive course that shows how you can build a stylish web app with machine learning at the backend to predict the future price of any cryptocurrency. The main course has a mini crash course on Python for newbies and culminates into the theory and practice of Machine Learning and its predictive modeling application on cryptocurrencies.
At the end of this course, you will be able to develop a full-fledged web app that will take in data (available for free on the Internet). As you will provide the data to the web app, the web app having its predictive machine learning model at the backend will spit out the future prices of a cryptocurrency.
The course includes all the code for the web app, and with a tiny tuning in the code, you can adjust the web app to predict the prices of any cryptocurrency. And for any number of days in the future (recommended not to proceed more than 10-15 days for accuracy).
All the tools, software, and data used in the course can be downloaded for free and put to use instantly.
This course builds Machine Learning models from three popular algorithms. With Python code taking advantage of the predictive nature of machine learning, that can detect patterns in data that humans are not capable of doing. All the models go through evaluation for their accuracy before deployment.
I hope you will be able to build bigger, better, more efficient, and more effective models and web apps to predict cryptocurrency future prices with more accuracy.Â Â Â
Who this course is for:
Python Programmers, Data Scientist, Algorithmic Traders, AI Engineers, Computer Programmers, Cryptocurrency junkies and enthusiasts, Machine Learning Engineers who want to learn to predict future cryptocurrency prices.

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Python

Machine Learning

Bitcoin Trading

Tauqeer Khurram

Instructor's Courses

An IT professional and SEO Writer with 21 years of solid experience in Information Technology. I have created my first program when I was 15 years old. It was in BASICA programming language.I have worked as an IT professional for many top Middle Eastern and South Asian companies, and I have been playing with computers for around 34 years.

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