What's next - Python Tutorial

Contents

• Introduction Introduction

  • Algorithmic trading using machine learning

    37s
  • Maximize your learning

    3m 8s
• 1. Working with Stock Market Data 1. Working with Stock Market Data

  • Download and export data

    5m 56s
  • (Locked)
    Filter rows and create columns for trading strategies

    6m 10s
• 2. Backtesting with Classification Models 2. Backtesting with Classification Models

  • Compute machine learning classification model

    9m 12s
  • (Locked)
    First configurations of the strategy class

    4m 34s
  • (Locked)
    Simulate the investment strategy step by step

    4m 37s
  • (Locked)
    Run the backtest on the strategy

    4m 17s
  • (Locked)
    Challenge: Backtest with other tickers

    3m 42s
• 3. Backtesting with Regression Models 3. Backtesting with Regression Models

  • (Locked)
    Compute machine learning regression model

    2m 56s
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    How to evaluate regression models

    5m
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    Configure and run the backtest with the regression model

    1m 47s
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    How to interpret the backtesting dashboard

    5m 36s
• 4. Backtesting Optimization 4. Backtesting Optimization

  • (Locked)
    Optimizing strategy parameters

    4m 43s
  • (Locked)
    Pandas reporting with heatmaps

    2m 23s
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    Smart optimization to save computing time

    4m 13s
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    Challenge: Optimization with other datasets

    3m 41s
• 5. The Overfitting Problem in Backtesting 5. The Overfitting Problem in Backtesting

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    Why machine learning models overfit the data

    4m 21s
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    How to train models within the backtest

    2m 47s
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    Challenge: Train test with other tickers

    3m 5s
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    Walk forward validation in machine learning

    8m 31s
  • (Locked)
    Anchored walk forward validation in backtesting

    5m 36s
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    Create library for backtesting strategies

    2m 50s
  • (Locked)
    Interpret reports from walk forward validation approaches

    1m 12s
  • (Locked)
    Challenge: Walk forward with other tickers

    5m 2s
• Conclusion Conclusion

  • (Locked)
    Course summary

    7m 11s
  • (Locked)
    What's next

    55s