About this Course
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100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 7 hours to complete

Suggested: 5 - 7 hours per week...

English

Subtitles: French, Portuguese (Brazilian), German, English, Spanish, Japanese...

Skills you will gain

TensorflowBigqueryMachine LearningData Cleansing

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 7 hours to complete

Suggested: 5 - 7 hours per week...

English

Subtitles: French, Portuguese (Brazilian), German, English, Spanish, Japanese...

Syllabus - What you will learn from this course

Week
1
9 minutes to complete

Introduction

2 videos (Total 9 min)
2 videos
Intro to Qwiklabs5m
1 hour to complete

Practical ML

10 videos (Total 62 min), 1 quiz
10 videos
Supervised Learning5m
Regression and Classification11m
Short History of ML: Linear Regression7m
Short History of ML: Perceptron5m
Short History of ML: Neural Networks7m
Short History of ML: Decision Trees5m
Short History of ML: Kernel Methods4m
Short History of ML: Random Forests4m
Short History of ML: Modern Neural Networks8m
1 practice exercise
Module Quiz6m
1 hour to complete

Optimization

13 videos (Total 60 min), 1 quiz
13 videos
Defining ML Models4m
Introducing the Natality Dataset6m
Introducing Loss Functions6m
Gradient Descent5m
Troubleshooting a Loss Curve2m
ML Model Pitfalls6m
Lab: Introducing the TensorFlow Playground6m
Lab: TensorFlow Playground - Advanced3m
Lab: Practicing with Neural Networks6m
Loss Curve Troubleshooting1m
Performance Metrics3m
Confusion Matrix5m
1 practice exercise
Module Quiz6m
3 hours to complete

Generalization and Sampling

9 videos (Total 64 min), 3 quizzes
9 videos
Generalization and ML Models6m
When to Stop Model Training5m
Creating Repeatable Samples in BigQuery6m
Demo: Splitting Datasets in BigQuery8m
Lab Introduction1m
Lab Solution Walkthrough9m
Lab Introduction2m
Lab Solution Walkthrough23m
1 practice exercise
Module Quiz12m
3 minutes to complete

Summary

1 video (Total 3 min)
1 video
4.6
349 ReviewsChevron Right

43%

started a new career after completing these courses

44%

got a tangible career benefit from this course

29%

got a pay increase or promotion

Top reviews from Launching into Machine Learning

By PTDec 2nd 2018

This is an awesome module. It will open up so much inside story of ML process which is core of the topic with such a simplicity. It greatly increases my interest into this topic and this course :)

By PAAug 4th 2018

Good course, covering all the basics about machine learning and most importantly, everything that surrounds an ml project and you need to take into account to make your ml project successful.

About Google Cloud

We help 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....

About the Machine Learning with TensorFlow on Google Cloud Platform Specialization

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 features in a way that allows ML to learn important characteristics from the data and bring human insight to bear on the problem. Finally, learn how to incorporate the right mix of parameters that yields accurate, generalized models and knowledge of the theory to solve specific types of ML problems. You will experiment with end-to-end ML, starting from building an ML-focused strategy and progressing into model training, optimization, and productionalization with hands-on labs using Google Cloud Platform. > By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <...
Machine Learning with TensorFlow on Google Cloud Platform

Frequently Asked Questions

  • Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

  • If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

  • Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

  • If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

  • This course is one of a few offered on Coursera that are currently available only to learners who have paid or received financial aid, when available.

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