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.
python,reinforcement learning,artificial intelligence,data science,development,ai for beginners
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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