Introduction to Neural Networks and Deep Learning
Expand your knowledge and skills in Neural Networks and Deep Learning with this online free course. Build and train deep neural networks for industry-related problems using key calculations that underlie deep learning tasks.
4.57
Intermediate
3.75 Hrs
66.2K+
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About this course
This free Neural Networks and Deep Learning course gives valuable insights into deep learning applications in various fields and a better understanding of the different frameworks used in neural network applications. You will discover and understand various deep learning concepts and get familiarized with Artificial Neural Network topics. You will also be walked through a few fundamental concepts covering things like the history of the subject and the need to learn it. Further, you will study CNN, RNN, and LSTM and compare types of chatbots and conventional interfaces, Machine learning, and Deep Learning. Earn a certificate for this course after completing the assigned quiz. Begin your learning journey in this leading domain of Neural Networks and Deep Learning by registering for the Machine Learning courses with millions of aspirants across the globe after you have learned from this self-paced intermediate-level guide!
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Course Outline
What is Deep Learning?
This module introduces you to the term “Deep Learning”, and you will go through its definition and an example to get an overview.
Where does DL Fit?
This module explains the Deep Learning cascade and its hierarchy with Machine Learning and Artificial Intelligence.
Where to use DL?
This module explains the widespread applications of Deep Learning in the Finance, Healthcare, Social Media, and Automation industry.
Brief History
This module articulates Deep Learning and discusses its history since the technology emerged.
ML vs. DL
Deep Learning is the subset of Machine Learning, and through this module, you will understand the fine line between Machine Learning and Deep Learning. In order to help you understand it better, you will go through a car classification example.
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