Udemy - Algorithmic Trading with Python - Machine Learning strategies

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[ CourseMega.com ] Udemy - Algorithmic Trading with Python - Machine Learning strategies
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1. Introduction
    • 1. Introduction.html (1.0 KB)
    2. Basics of python
    • 1. Introduction.mp4 (10.4 MB)
    • 1. Introduction.srt (1.3 KB)
    • 10. Python structures For.mp4 (29.9 MB)
    • 10. Python structures For.srt (4.3 KB)
    • 11. Python structures While.mp4 (14.3 MB)
    • 11. Python structures While.srt (2.2 KB)
    • 12. Functions Basics of function.mp4 (32.7 MB)
    • 12. Functions Basics of function.srt (4.7 KB)
    • 13. Functions Local variable.mp4 (14.3 MB)
    • 13. Functions Local variable.srt (1.8 KB)
    • 14. Functions Global variable.mp4 (12.8 MB)
    • 14. Functions Global variable.srt (1.3 KB)
    • 15. Functions Lambda function.mp4 (13.2 MB)
    • 15. Functions Lambda function.srt (1.7 KB)
    • 2. Type of object Number.mp4 (24.0 MB)
    • 2. Type of object Number.srt (3.4 KB)
    • 3. Type of object String.mp4 (83.7 MB)
    • 3. Type of object String.srt (8.6 KB)
    • 4. Type of object Logical Operations and Boolean.mp4 (25.7 MB)
    • 4. Type of object Logical Operations and Boolean.srt (3.9 KB)
    • 5. Type of object Variable assignment.mp4 (37.0 MB)
    • 5. Type of object Variable assignment.srt (5.0 KB)
    • 6. Type of object Tuple and List.mp4 (49.8 MB)
    • 6. Type of object Tuple and List.srt (6.7 KB)
    • 7. Type of object Dictionary.mp4 (46.7 MB)
    • 7. Type of object Dictionary.srt (5.8 KB)
    • 8. Type of object Set.mp4 (28.7 MB)
    • 8. Type of object Set.srt (3.7 KB)
    • 9. Python structures If Elif Else.mp4 (41.0 MB)
    • 9. Python structures If Elif Else.srt (5.1 KB)
    3. Basics of Python for Data Science
    • 1. Introduction.mp4 (5.2 MB)
    • 1. Introduction.srt (0.7 KB)
    • 10. Matplotlib Tools.mp4 (17.6 MB)
    • 10. Matplotlib Tools.srt (2.0 KB)
    • 2. Numpy Array.mp4 (60.1 MB)
    • 2. Numpy Array.srt (9.0 KB)
    • 3. Numpy Random.mp4 (14.1 MB)
    • 3. Numpy Random.srt (5.6 KB)
    • 4. Numpy Indexing slicing Transformation.mp4 (85.4 MB)
    • 4. Numpy Indexing slicing Transformation.srt (10.9 KB)
    • 5. Pandas Serie and DataFrame.mp4 (31.3 MB)
    • 5. Pandas Serie and DataFrame.srt (4.1 KB)
    • 6. Pandas Cleaning and selection data.mp4 (81.6 MB)
    • 6. Pandas Cleaning and selection data.srt (10.0 KB)
    • 6.1 assets.csv (3.1 MB)
    • 7. Pandas Conditional selection.mp4 (26.0 MB)
    • 7. Pandas Conditional selection.srt (3.0 KB)
    • 8. Matplotlib Graph.mp4 (19.7 MB)
    • 8. Matplotlib Graph.srt (1.9 KB)
    • 9. Matplotlib Scatter.mp4 (14.3 MB)
    • 9. Matplotlib Scatter.srt (1.5 KB)
    4. Import financial data
    • 1. Introduction Install library on google colab.mp4 (10.9 MB)
    • 1. Introduction Install library on google colab.srt (1.1 KB)
    • 2. Import the data.mp4 (48.2 MB)
    • 2. Import the data.srt (4.2 KB)
    • 3. Strengths and weaknesses of yfinance.mp4 (17.8 MB)
    • 3. Strengths and weaknesses of yfinance.srt (2.7 KB)
    5. Financial features engineering
    • 1. Introduction.mp4 (21.5 MB)
    • 1. Introduction.srt (2.2 KB)
    • 2. Get stock prices.mp4 (16.6 MB)
    • 2. Get stock prices.srt (2.1 KB)
    • 3. Create a simple moving average (SMA).mp4 (43.0 MB)
    • 3. Create a simple moving average (SMA).srt (3.9 KB)
    • 4. Create a moving standard deviation (MSD).mp4 (20.6 MB)
    • 4. Create a moving standard deviation (MSD).srt (2.2 KB)
    • 5. Use the technical analysis library to create a RSI indicator.mp4 (30.0 MB)
    • 5. Use the technical analysis library to create a RSI indicator.srt (3.2 KB)
    • 6. Automatisation of the features engineering process.mp4 (19.2 MB)
    • 6. Automatisation of the features engineering process.srt (2.0 KB)
    6. Linear regression algorithm
    • 1. Introduction.mp4 (7.1 MB)
    • 1. Introduction.srt (0.7 KB)
    • 2. Linear Regression Theory.mp4 (24.8 MB)
    • 2. Linear Regression Theory.srt (3.3 KB)
    • 3. Import the data.mp4 (4.3 MB)
    • 3. Import the data.srt (1.4 KB)
    • 4. Split the dataset.mp4 (31.0 MB)
    • 4. Split the dataset.srt (3.2 KB)
    • 5. Linear Regression Practice.mp4 (19.8 MB)
    • 5. Linear Regression Practice.srt (2.4 KB)
    • 5.1 Extract_Chapter_7.pdf (289.0 KB)
    • 6. Predict stock prices using Machine learning predictions.mp4 (20.0 MB)
    • 6. Predict stock prices using Machine learning predictions.srt (2.0 KB)
    • 7. Create trading strategies using Machine learning predictions.mp4 (29.3 MB)
    • 7. Create trading strategies using Machine learning predictions.srt (4.2 KB)
    • 8. Automatize the process.mp4 (29.2 MB)
    • 8. Automatize the process.srt (3.4 KB)
    7. Vectorized Backtesting
    • 1. Introduction.mp4 (7.4 MB)
    • 1. Introduction.srt (1.0 KB)
    • 2. Sortino ratio computation.mp4 (57.4 MB)
    • 2. Sortino ratio computation.srt (5.9 KB)
    • 3. Beta ratio computation (CAPM metric).mp4 (72.7 MB)
    • 3. Beta ratio computation (CAPM metric).srt (7.2 KB)
    • 4. Alpha ratio computation (CPAM metric).mp4 (23.6 MB)
    • 4. Alpha ratio computation (CPAM metric).srt (2.4 KB)
    • 5. Drawdown function creation.mp4 (28.7 MB)
    • 5. Drawdown function creation.srt (3.0 KB)
    • 6. Drawdown function application.mp4 (27.4 MB)
    • 6. Drawdown function application.srt (2.8 KB)
    • 7. BackTesting Function.mp4 (21.2 MB)
    • 7. BackTesting Function.srt (2.1 KB)
    • 8. Backtesting Function Customize.mp4 (24.2 MB)
    • 8. Backtesting Function Customize.srt (2.2 KB)
    • 9. Application Machine learning.mp4 (14.3 MB)
    • 9. Application Machine learning.srt (1.4 KB)
    8. Support vecteur machine

Description

Algorithmic Trading with Python: Machine Learning strategies



https://CourseMega.com

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 69 lectures (5h 2m) | Size: 1.67 GB
Artificial intelligence / Machine Learning for algorithmic trading. MetaTrader 5 bots included!
What you'll learn:
Machine learning skills
MT5 live trading
Create algorithmic trading strategies using Machine Learning
Manage data using Pandas
Data Cleaning using Pandas
Python programmation
Compare / choose trading strategies
Understand and implement a Linear Regression
Understand and implement a SVM
Understand and implement a PCA
Import stock prices from your broker
Import stock prices from Yahoo Finance
Put your strategy on a VPS

Requirements
Some python knowledge are welcoming but not necessary

Description
You already know python, and you want to monetize and diversify your knowledge?

You already have some trading knowledge, and you want to learn about artificial intelligence in algorithmic trading?



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Udemy - Algorithmic Trading with Python - Machine Learning strategies


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1.8 GB
seeders:13
leechers:7
Udemy - Algorithmic Trading with Python - Machine Learning strategies


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