AI: Reinforcement Learning in Python
Provides learners with the necessary skills to implement advanced AI concepts and practical applications through an examination of reinforcement learning.
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Description for AI: Reinforcement Learning in Python
Comprehensive Reinforcement Learning Topics: This section encompasses fundamental concepts, including the multi-armed bandit problem, Markov Decision Processes (MDPs), Dynamic Programming, Monte Carlo methods, Temporal Difference (TD) Learning, and Approximation Methods.
Practical Implementation Guidance and Zero Code Modifications: Learn to employ reinforcement learning algorithms with OpenAI Gym through hands-on learning.
Real-World Project: Utilize Q-Learning to construct a stock trading program in order to apply theoretical knowledge to a tangible, high-impact project.
Algorithm Implementation from Scratch: By autonomously coding machine learning algorithms, one can gain a more profound understanding, highlighting the significance of creating rather than relying on pre-built libraries.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 6
Offered by: On Udemy provided by Lazy Programmer Inc.
Duration: 14h 41m
Schedule: Full Lifetime Access
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