Description
Machine Learning for Stock and Crypto Trading – Python is the name of the Machine Learning for Stock and Crypto Trading with Python course, published by Udemy Academy. This course teaches you how to excel in financial trading by applying machine learning techniques to financial data using Python. This course does not cover a lot of in-depth theory. This is a very practical course, with high-level theory, aimed at anyone who can easily grasp the basic concepts, but more importantly, understand the program and use it immediately. If you are looking for a course with a lot of math, this course is not for you. If you are looking for a course to experiment with using financial data in a fun, exciting, and potentially profitable way, you will probably really enjoy this course.
What you will learn in the Machine Learning Applied to Stocks and Crypto Trading – Python course:
- Understand hidden states and regimes for any market or asset using hidden Markov models
- Discover the optimal assets for trading ETFs, stocks, forex or cryptocurrencies using K-Means Clustering
- Compress information from a large set of indicators with PCA
- Make objective future predictions on financial data with XGBOOST
- Train a Reinforcement Learning AI Model for Stock Trading with PPO
- Determine market efficiency on each asset
- Learn about Python libraries including pandas, PyTorch (for deep learning), and sklearn.
Course Details
Editor: Udemy
Instructor: Shaun McDonogh
French language
Education Level: Introductory to Advanced
Number of lessons: 111
Teaching duration: 17 hours and 49 minutes
Course titles
Course prerequisites
You should have some basic experience with Python
You must be aware of the concepts related to trading like pairs trading
You need to know about assets such as ETFs, VIX, stocks and cryptocurrencies.
course images
Course introduction video
Remarks
After ripping, view with your favorite player.
Subtitle: English
Quality: 720p
Changes:
Version 2024/2 compared to 2022/7 increased the number of 3 lessons and the duration by 25 minutes. English subtitles have also been added to the course.
Download link
Password of the file(s): www.downloadly.ir
size
8.51 GB