Your smartphone, smartwatch, and automobile (if it is a newer model) have AI (Artificial Intelligence) inside serving you every day. In the near future, more advanced “self-learning” capable DL (Deep Learning) and ML (Machine Learning) technology will be used in almost every aspect of your business and industry. So now is the right time to learn what DL and ML is and how to use it in advantage of your company. This course has three parts, where the first part focuses on DL and ML technology based future business strategy including details on new state-of-the-art products/services and open source DL software, which are the future enablers. The second part focuses on the core technologies of DL and ML systems, which include NN (Neural Network), CNN (Convolutional NN), and RNN (Recurrent NN) systems. The third part focuses on four TensorFlow Playground projects, where experience on designing DL NNs can be gained using an easy and fun yet very powerful application called the TensorFlow Playground. This course was designed to help you build business strategies and enable you to conduct technical planning on new DL and ML services and products.
About this Course
Learner Career Outcomes
Learner Career Outcomes
Yonsei University was established in 1885 and is the oldest private university in Korea.
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TOP REVIEWS FROM DEEP LEARNING FOR BUSINESS
It was very informative, the instructor paces the information very well, & I love the resources at the end of every lecture. the last project section was very well done & explained in detail.
Even though I do not have the background of Computer Engineering or Science I was able to understand from the professor and the final project truly was able to explain everything for me.
Amazing lectures! Detailed description of each topic coupled with mind blowing graded assignments! :) Thanks a real bunch, Coursera for offering this courses & of course, scholarship!
Good Introductory course for those from a business background. But if you have technical skills, then probably another course (Machine Learning from Andrew Ng may be a better one).
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