Intro to TensorFlow

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

( 180 Reviews )

Created by: Google Cloud Training

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Overall Score : 80 / 100

Course Description

We introduce low-level TensorFlow and work our way through the necessary concepts and APIs so as to be able to write distributed machine learning models. Given a TensorFlow model, we explain how to scale out the training of that model and offer high-performance predictions using Cloud Machine Learning Engine.Course Objectives:Create machine learning models in TensorFlowUse the TensorFlow libraries to solve numerical problemsTroubleshoot and debug common TensorFlow code pitfallsUse tf.estimator to create, train, and evaluate an ML modelTrain, deploy, and productionalize ML models at scale with Cloud ML EngineCOMPLETION CHALLENGEComplete any GCP specialization from November 5 - November 30, 2019 for an opportunity to receive a GCP t-shirt (while supplies last). Check Discussion Forums for details.

Time: 10h

Instructor Details

Google Cloud Training

4.0 Rating
180 Reviews

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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4.0

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By Bopeng Z on 3-Oct-18

Please some extra advance concept

By Aleksander Z on 7-Oct-18

Great course as an introduction to TF, however, the labs are not as in depth as I'd have liked. Nonetheless, the course is well executed by the presenters.

By Karthik R on 26-Sep-18

Challenge problems at the end of each assignment are really good, however, there should be videos showing how the instructors would solve them, I would be fine watching 30 min videos describing the solutions. Nice course!

By Gerardo S on 22-Sep-18

really enjoyed course - good insight

By Aaditya A on 3-Dec-18

Good course! Sometimes I was not 100% sure what I was supposed to do. But the solution videos made it clear afterwards.

By Muzaffar H on 9-Jul-19

Love this course. One of the best course in this specialization. Very informative content.

By Handong D B on 6-Jul-19

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

By Abhishek B on 6-Jul-19

An interesting course on the basics TensorFlow Estimators and Google Cloud Machine Learning engine.

By Tiberiu D O on 26-Mar-19

Amazing

By Rodrigo P on 22-Mar-19

Good explanation, It will be better if this class could provide slides so that we do not need to take screenshoot all the time...

By Vadim K on 7-Mar-19

It really helped me to get a grasp of Tensorflow. Now things are quite understandable for me.

By Gopinath V on 3-Mar-19

Knowing about the power of tensorflow estimators was amazing.

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Video Duration: 10h
Price: Free 0 Track Price
Provider: Coursera
University: Google Cloud
Language: English
Certificate: Yes

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