Practical AI with Python and Reinforcement Learning is a very practical and valuable training course focusing on artificial intelligence and systemic learning techniques published by Udemi Academy. In this course, you will become familiar with Reinforcement Learning techniques and methods and design a practical and responsive AI.
Reinforcement learning is one of the machine learning trends that is inspired by behavioral psychology. This method focuses on behaviors that enhance the performance of the machine by providing various rewards and steer in a specific direction. The machines and systems created with this technique have a very powerful neural network and can perform difficult and complex tasks that challenge even human intelligence.
In this course, the Python programming language, which is one of the most widely used and famous programming languages, has been used to develop artificial intelligence. The educational approach of this course is completely project-oriented, and at the end of this course, you will be able to build artificial intelligence to respond to various problems, issues, challenges, and situations.
In the beginning, you cross the open-source software ( Keras ) and Tnsvrflv ( Tensorflow ) will learn that in designing neural networks and deep learning and machine learning applications. Among the most important educational topics of this course are artificial neural networks, torsional or convergent neural networks, classical Q-learning, deep reinforcement learning, SARSA algorithm, cross-entropy methods, and…
What you will learn in Practical AI with Python and Reinforcement Learning:
- Build a powerful AI-based on reinforcement learning techniques using the Python programming language
- Build a torsional neural network using TensorFlow to work on different images
- Use the OpenAI platform to set up a personalized AI development environment
- Deep Q-Learning
- Using Cross-Entropy Methods to Build Artificial Intelligence Based on Reinforcement Learning Techniques
- Build an artificial neural network with TensorFlow
- Build an intelligent agent using artificial intelligence
- Implementation of SARSA algorithm
- And …
Instructor: Jose Portilla
Education Level: Advanced
Number of Courses: 124
Training Duration: 21 hours and 36 minutes
Course topics on 2021/9
Prerequisites for Practical AI with Python and Reinforcement Learning
You should be very comfortable with basic Python and installing Python libraries.
This is NOT a course for beginners, we highly suggest you take our “Data Science and Machine Learning Masterclass” first!
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