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Part 15 (1:39:38) ============ 27. Working with two or many Strategies (Combination) 0:00:00 2. Strategy 1 SMA 0:02:17 3. Strategy 2 Mean Reversion 0:04:43 4. Combining both Strategies - Alternative 1 0:10:05 5. Taking into account busy Trading Hours 0:12:37 6. Strategy Backtesting 0:14:18 7. Combining both Strategies - Alternative 2 0:17:07 8. Strategy Optimization 28. A Machine Learning-powered Strategy A-Z (DNN) 0:26:00 1. Project Overview 0:31:32 3. Installation of Tensorflow & Keras (Part 2) 0:39:24 4. Getting and Preparing the Data 0:40:38 5. Adding LabelsFeatures 0:46:15 6. Adding lags 0:48:41 7. Splitting into Train and Test Set 0:50:41 8. Feature ScalingEngineering 0:53:58 9. Creating and Fitting the DNN Model 1:01:59 10. Prediction & Out-Sample Forward Testing 1:09:01 11. Saving Model and Parameters 1:11:54 13. Implementation (Oanda & FXCM) 29. Error Handling How to make your Trading Bot more stable and reliable 1:24:19 1. Introduction 1:29:25 3. Python Errors (Exceptions) 1:31:06 4. try and except 1:33:45 5. Catching specific Errors 1:35:15 6. The Exception class 1:36:20 7. try, except, else
