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.
Acerca de este Curso
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Principales reseñas sobre DEEP LEARNING AND REINFORCEMENT LEARNING
The concepts were clearly explained in lectures. The assignments were very helpful to gain a practical insight of the skills learned in the course.
Hello, thank you again for the course. My congrats, once more, to the instructor on the videos!
The difficult terms are simplified enough for understanding and application in real life.
Reinforcement Learning part needs to be a separate course and more details in it
Acerca de Certificado profesional de Aprendizaje automático de IBM
Machine Learning is one of the most in-demand skills for jobs related to modern AI applications, a field in which hiring has grown 74% annually for the last four years (LinkedIn). This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Machine Learning and leverage the main types of Machine Learning: Unsupervised Learning, Supervised Learning, Deep Learning, and Reinforcement Learning. It also complements your learning with special topics, including Time Series Analysis and Survival Analysis.