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LifestyleArt and Science of Machine Learning
What is machine learning, and what kinds of problems can it solve? What are the five phases of converting a candidate use case to be driven by machine learning, and why is it important that the phases not be skipped? Why are neural networks so popular now? How can you set up a supervised learning problem and find a good, generalizable solution using gradient descent and a thoughtful way of creating datasets? Learn how to write distributed machine learning models that scale in Tensorflow, scale out the training of those models. and offer high-performance predictions. Convert raw data to feature
Created by: Google Cloud Training
Quality Score
Overall Score : 88 / 100
Course Description
Instructor Details
- 4.4 Rating
75 Reviews
Google Cloud Training
The Google Cloud Training team is responsible for developing, delivering and evaluating training that enables our enterprise customers and partners to use our products and solution offerings in an effective and impactful way. Google Cloud helps millions of organizations empower their employees, serve their customers, and build what's next for their businesses with innovative technology created in-and for-the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
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Reviews
By Super-intelligent S o t C B on 14-Nov-19
Good course, but I couldn't get over the Estimator API. IMHO it's too complicated compared to Keras and I just could not force myself to care about it.
By Muhammad Z H on 24-Oct-19
Thanks Professor
By Pratik S on 21-Oct-19
complete hyper parameters is given in lab
By James W on 27-Sep-19
Good class with a lot of information and new terminology thrown at you. Especially if you don't have a machine learning background. The labs are done in a way where you can get familiar with TensorFlow and Python programming, without having to know Python programming. Good intro if you want to be familiar with GCP ML. If you're looking to write a bunch of code this will probably not be enough for you.
By sumeyra d on 9-Sep-19
Advanced and detailed course for accurate tensorflow models
By Ayush T on 6-Sep-19
This course is of specialization is the most applicable in the case of my work. If customer estimator was explained in the earlier courses, many other experiments with our own custom estimators could have been tried.
By Manish K on 28-Aug-19
great
By Mr. J on 27-Aug-19
Now that's what I am talking about. Great survey on nuts and bolts of ML practicalities. The how and why of model generation and manipulation. Very excellent. Super library of reference models and materials.
By Naman M on 19-Aug-19
Awesome
By Ruslan A on 16-Aug-19
Many notebooks contain some typo/erros.
By Manish G on 30-Jul-19
The course is quite good and have balance of theory and labs. It is useful course for beginners.
By Nhan T N on 25-Jul-19
Great course for essential techniques in ML model design.
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- Video Duration:
8h - Provider: Coursera
- University:
Google Cloud - Language:
English - Certificate:
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