Sequences, Time Series and Prediction
Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework.In this four-course Specialization, you'll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network's performance using convolutions as you train it to identify real-world images. You'll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input
Created by: Laurence Moroney
Quality Score
Overall Score : 86 / 100
Course Description
Instructor Details
- 4.3 Rating
111 Reviews
Laurence Moroney
Laurence Moroney is a Developer Advocate at Google working on Artificial Intelligence with TensorFlow. As the author of more programming books than he can count, he's excited to be working with deeplearn.ai and Coursera in producing video training. When not working with technology, he's a member of the Science Fiction Writers of America, having authored several science fiction novels, a produced screenplay and comic books, including the prequel to the movie 'Equilibrium' starring Christian Bale. Laurence is based in Washington State, where he drinks way too much coffee.
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Reviews
By Slav K on 13-Nov-19
As from fulltime ML practitioner and occasional user of TF this course is not too much in "practice" as many things are left untouched. However can be beneficial to complete newbie.
By David R on 11-Nov-19
It's a bit of an insult to call this thing a "course". The entire video material is maybe a bit over 1 hour for the entire "4 weeks". The quizzes (1 quiz per week) are ridiculously easy, and the (ungraded) exercises are basically - "do what we did in the lecture, only from memory".The material itself is good, but doesn't go in depth. They introduce Huber loss, and then tell you to go read about it in Wikipedia. Overall - low quality. Would have been great as a first week in a real "mini course" (DeepLearning specialization style), or one lecture, in a real academic course. Disappointed.
By Yingnan X on 28-Oct-19
The homework exercise seems to heavily overlap with the demo notebook that I can simply copy and paste the code into the exercise notebook. It would be great if in the future the exercise can be a little harder and involve more thinking.
By Hannan S on 28-Oct-19
First of all, the course was amazing! I found it great for the following reasons:- Laurence Moroney (Instructor) was very professional and clear while delivering the knowledge- The introductions by Andrew NG were really nice- Easy to understand codes and understanding of thr underlying principles- Varied topics such as CNN, NLP & Time Series- Very insightful by providing expert opinions about different ways of model optimizationI really enjoyed the course and I thank the instructor for the same :)
By charles l on 23-Oct-19
This specialization was the ideal evolution in my DNN training after having taken Andrew Ng's classic ML course, followed by the deeplearning.ai DNN specialization. The instructor is excellent, as are the lecture notes, training materials, coding platform and examples! I am moving on to Advanced ML w/ TensorFlow on Google Cloud
By Michael B on 20-Oct-19
I absolutely love the deeplearning.ai courses. I previously took Andrew's course that went more into the theory, and this course was a fantastic compliment to it that focused more on putting deep learning concepts into practice via tensorflow. I look forward to any future courses they put out! :D
By Bridget T on 14-Oct-19
Nice course, I achieved more from this course about sequence model. Thank so much!
By Akhil K P on 11-Oct-19
It is a very good ready to go and really a practical example driven Course.
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