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Reinforcement Learning for Trading
Coursera
Course
Unknown

Reinforcement Learning for Trading

New York Institute of Finance

This course introduces reinforcement learning techniques for developing and optimizing trading strategies using neural networks and LSTM.

Unknown3 weeksEnglish

About this Course

In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data. By the end of the course, you will be able to build trading strategies using reinforcement learning, differentiate between actor-based policies and value-based policies, a

What You'll Learn

  • Understand reinforcement learning strategies structure and techniques
  • Identify benefits of reinforcement learning over other methods
  • Describe steps to develop and test RL trading strategies
  • Explain methods to optimize RL trading strategies

Instructors

J

Jack Farmer

New York Institute of Finance

Topics

Artificial Intelligence and Machine Learning (AI/ML)
Reinforcement Learning
Risk Management
Financial Market
Deep Learning
Time Series Analysis and Forecasting
Portfolio Risk
Artificial Neural Networks
Portfolio Management
Financial Trading

Course Info

PlatformCoursera
LevelUnknown
PacingUnknown
PriceFree

Skills

الذكاء الاصطناعي وتعلم الآلة
التعلم التعزيزي
إدارة المخاطر
السوق المالية
التعلم العميق
تحليل وتوقع السلاسل الزمنية
مخاطر المحفظة
الشبكات العصبية الاصطناعية
Portfolio Management
Financial Trading

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