AI in Trading: Signal Creation

سرفصل های دوره

Build AI Based Buy/Sell Signal/Indicator in Your Algorithmic Trading Bot, Boost Your Python Machine Learning Knowledge

1. Fundamental

1. Introduction

2. Trading Concepts

3. Trading Process

4. Machine Learning Basics

5. Machine Learning in Trading

2. Basic Python Packages

1. Introduction

2. Jupyter

3. Jupyter Tour

4. Pandas and Numpy

5. Numpy Basics

6. Pandas Basics

7. Plotting

8. Seaborn and MatPlotLib

3. Data Sources

1. Introduction

2. Types of Data

3. Methods to Access Data

4. Alpha Vantage

5. Alpha Vantage Access Data With Python

6. AlphaVantage Big Range

7. MetaTrader

8. Metatrader Access Data With Python

4. Feature and Target Design

1.1 av AAPL.csv

1. Introduction

2. Feature and Target Extraction

3. Data Usage Considerations

4. PandasTa

5. PandasTa Target Design

6. PandasTa Feature Feature Design

7. Visualizing Features and Targets

8. Visualizing Features and Targets Continuation

5. Probability Based Algorithms (Bayesian)

1.1 features targets.csv

1. Introduction

2. Bayesian Mindset

3. Bayesian Mathematics

4. Bayesian Application in Spam Detection

5. Bayesian For Parameter Estimation

6. Bayesian For Parameter Estimation Cont.

7. Pymc

8. Pymc Basics

9. Parameter Estimation using Pymc

10. Classification vs Regression

11. Conver Returns to Classification

12. Bayesian Log Regression

13. Bayesian Log Regression for Price Direction in Python

14. Bayesian Log Regression for Price Direction in Python Cont.

6. Decision Tree

1.1 features targets.csv

1. Introduction

2. Decistion Tree Basics

3. Decistion Tree Regression

4. Decistion Tree to Estimate Returns

5. Decistion Tree to Estimate Returns Cont.

6. Decistion Tree to Estimate Returns Cont.

7. Decistion Tree with All Features

8. Split Train and Test

9. Decision Tree for Classification

10. Decision Tree for Classification All Features

11. Cross Validation

12. Cross Validation with Python

13. Cross Validation with Python Cont.

14. Tuning Decision Tree

15. Train Size Selection

16. Random Forest

17. Random Forest with Python

18. Random Forest Tuning

7. Gradient Boosting

1.1 features targets.csv

1. Introduction

2. Ensemble

3. DT Boosting

4. Boosting with Test data

5. Boosting Cross Validation

6. Boosting Cross Validation Cont.

8. Deep Learning

1.1 features targets.csv

1. Introduction

2. Deep Learning

3. What is Gradient Descent

4. Feed Forward Neural Network

5. Feed Forward Neural Network Tensorflow

6. Feed Forward Neural Network Hyperparameter Tuning

7. Feed Forward Neural Network Hyperparameter Tuning Cont.

9. Recurrent Neural Network

1.1 features targets.csv

1. Introduction

2. Recurrent Neural Network and LSTM

3. Data Preparation

4. LSTM with Tensorflow

5. LSTM Model Diagnosis

6. LSTM Model Diagnosis Cont.

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تولید کننده: Udemy