This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised Learning, and is frequently used to power most of the AI applications that we use on a daily basis. First you will learn about the theory behind Neural Networks, which are the basis of Deep Learning, as well as several modern architectures of Deep Learning. Once you have developed a few Deep Learning models, the course will focus on Reinforcement Learning, a type of Machine Learning that has caught up more attention recently. Although currently Reinforcement Learning has only a few practical applications, it is a promising area of research in AI that might become relevant in the near future.
- 5 stars72.03%
- 4 stars16.94%
- 3 stars7.62%
- 2 stars1.69%
- 1 star1.69%
DEEP LEARNING AND REINFORCEMENT LEARNING からの人気レビュー
Reinforcement Learning part needs to be a separate course and more details in it
The difficult terms are simplified enough for understanding and application in real life.
The core concepts of Deep Learning are explained well in this course.
Very good. I learned a lot but the subject matter is quite extensive.