NeuroEvolution of Augmenting Topologies NEAT Neural Networks
NeuroEvolution of Augmenting Topologies NEAT Neural Networks, available at $39.99, has an average rating of 3.8, with 8 lectures, based on 34 reviews, and has 588 subscribers.
You will learn about Understand the mechanisms of genetic algorithms Understand the mechanisms of the NeuroEvolution of Augmenting Topologies algorithm Evolve NEAT-based artificial neural networks using NEAT-Python Apply NEAT to various control and computer problems This course is ideal for individuals who are Beginner neural network, machine learning, or robotics researchers curious about the applicability of genetic algorithms to artificial neural networks It is particularly useful for Beginner neural network, machine learning, or robotics researchers curious about the applicability of genetic algorithms to artificial neural networks.
Enroll now: NeuroEvolution of Augmenting Topologies NEAT Neural Networks
Summary
Title: NeuroEvolution of Augmenting Topologies NEAT Neural Networks
Price: $39.99
Average Rating: 3.8
Number of Lectures: 8
Number of Published Lectures: 8
Number of Curriculum Items: 8
Number of Published Curriculum Objects: 8
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Understand the mechanisms of genetic algorithms
- Understand the mechanisms of the NeuroEvolution of Augmenting Topologies algorithm
- Evolve NEAT-based artificial neural networks using NEAT-Python
- Apply NEAT to various control and computer problems
Who Should Attend
- Beginner neural network, machine learning, or robotics researchers curious about the applicability of genetic algorithms to artificial neural networks
Target Audiences
- Beginner neural network, machine learning, or robotics researchers curious about the applicability of genetic algorithms to artificial neural networks
This is an introductory course to the NeuroEvolution of Augmenting Topologies algorithm. The course covers the most important concepts that characterize the NEAT algorithm, where a focus on understanding the theory behind genetic-algorithm-based artificial neural networks and their application to real-world problems, particularly in the fields of roboticsand control.
This course is intended for individuals from all backgrounds and knowledge levels, as it is structured such that there are no advanced prerequisites. From the fundamental concepts of neural networks to the unique mechanisms found in the algorithm, the lectures provide a succinct and complete overview of NEAT that can be understood by any researcher, academic, or self-learner.
The list of topics covered include:
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Introduction to neural networks
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Introduction to genetic algorithms
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Encoding
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Reproduction/crossover
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Mutation
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Speciation
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Dimensionality
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Implementation
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Application
This series also includes a tutorial on how to implement your own NEAT-based neural networks using a Python implementation of the algorithm. Only basic Python knowledge is required to get started on setting up the training environment and evolutionary process to procedurally generate efficient neural networks. All that is required is a simple code editor and your attention.
Taught by an academic researcher with advanced degrees, this course will familiarize you to NEAT, from how it works to how to use it to evolve your own neural networks.
Course Curriculum
Chapter 1: Background Theory
Lecture 1: Introduction to Neural Networks
Lecture 2: Introduction to Genetic Algorithms
Chapter 2: NEAT Theory
Lecture 1: Introduction to NEAT
Lecture 2: NEAT Encoding
Lecture 3: NEAT Innovation
Lecture 4: NEAT Speciation
Lecture 5: NEAT Dimensionality
Chapter 3: NEAT Application
Lecture 1: NEAT-Python
Instructors
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Ethan Kane
AI Engineer
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 1 votes
- 3 stars: 5 votes
- 4 stars: 14 votes
- 5 stars: 13 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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