How Google Does Machine Learning: Machine Learning With TensorFlow On Google Cloud Platform Specialization

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Machine Learning Course by Google:

The first course in Machine Learning with TensorFlow on Google Cloud Platform is How google does Machine Learning. In this course you can learn what is machine learning, and what types of problems can it solve? Google has been working differently about Machine Learning – about being logical rather than just manipulating data. Here it has been discussed about why such a determination is useful for data scientists when thinking about building a pipeline of machine learning models.

Then, there is a discussion about five steps to used convert a candidate use case to be driven by machine learning, and consider why it is important that the steps should not be skipped. At last we end with the recognition of biases that can enhance machine learning and how to recognize it. You can complete this course in less than 9 hours and is a 1-week course.

Then, there is a discussion about five steps to used convert a candidate use case to be driven by machine learning, and consider why it is important that the steps should not be skipped. At last we end with the recognition of biases that can enhance machine learning and how to recognize it. You can complete this course in less than 9 hours and is a 1-week course.

The skills that you can learn from this Machine Learning Course by Google are:

  • Application Programming Interfacing (API),
  • Inclusive Machine Learning (ML),
  • Machine Learning,
  • Google Cloud Platform,
  • Big-query

Once you complete this particular Machine Learning Course by Google, you will earn a certificate, which you can share it with your prospective employers and your professional network like LinkedIn. You can share your course certificate on printed resumes, CVs, or other documents in the Certification section of your LinkedIn profile.

Syllabus – How Google Does Machine Learning

Introduction to specialization

Introduces the specialization and the Google experts who will be teaching it.

  • Intro to ML on GCP Specialization – (Video) 1 min
  • Specialization Agenda – (Video) 5 min
  • Why Google? – (Video) 1 min
  • Why Google Cloud? – (Video) 2 min
  • Latest from Google – (Reading) 10 min
  • Module 1 Quiz – (Practice Exercise) 6 min

PLATFORM:

PROVIDER:

COST:

DIFFICULTY:

LANGUAGE:

CERTIFICATE:

EFFORT:

START DATE:

DURATION:

COURSERA

GOOGLE

FREE (AUDIT)

INTERMEDIATE

ENGLSIH

AVAILABLE

8 HOURS

ON GOING

1 WEEK

What it means to be AI first

You will learn what we mean when we say that Google’s company strategy is to be AI-first, and what that means in practice.

  • What it means to be AI first – (Video) 58 sec
  • Two stages of Machine Learning – (Video) 3 min
  • Machine Learning in Google Products – (Video) 5 min
  • Demo: ML in Google Photos – (Video) 1 min
  • Google Translate and Gmail – (Video) 1 min
  • Replacing Heuristic Rules – (Video) 5 min
  • It’s all about data – (Video) 3 min
  • Lab Intro – Framing an Machine Learning Problem – (Video) 1 min
  • Lab debrief – (Video) 4 min
  • Demo: Machine Learning in applications – (Video) 2 min
  • Pre-trained models – (Video) 3 min
  • The Machine Learning marketplace is evolving – (Video) 2 min
  • A data strategy – (Video) 5 min
  • Training and serving skew – (Video) 5 min
  • An Machine Learning strategy – (Video) 1 min
  • Transform your business – (Video) 2 min
  • Lab Intro – ML use case – (Video) 26 sec
  • Module 2 Quiz – (Practice Exercise) 6 min

How Google does Machine Learning

This module briefly describes the organizational know-how that Google has acquired over the years.

  • Introduction – (Video) 40 sec
  • Machine Learning Surprise – (Video) 4 min
  • The secret sauce – (Video) 8 min
  • Machine Learning and Business Processes – (Video) 6 min
  • The Path to Machine Learning – (Video) 10 min
  • End of phases deep dive – (Video) 4 min
  • Module 3 Quiz – (Practice Exercise) 6 min

Inclusive Machine Learning

This module will discuss why machine learning systems aren’t fair by default and some of the things you have to keep in mind as you infuse ML into your products.

  • Introduction – (Video) 1 min
  • Machine Learning and Human Bias – (Video) 2 min
  • Evaluating Metrics for Inclusion – (Video) 3 min
  • Statistical Measurements and acceptable tradeoffs – (Video) 4 min
  • Equality of Opportunity – (Video) 6 min
  • Simulating Decisions – (Video) 3 min
  • Finding Errors in your dataset using Facets – (Video) 4 min
  • Module 4 Quiz – (Practice Exercise) 6 min

Python notebooks in the cloud

This module covers Cloud DataLab, which is the development environment you will use in this specialization.

  • Module Introduction – (Video) 1 min
  • AI Platform Notebooks – (Video) 1 min
  • Demo: AI Platform Notebooks – (Video) 3 min
  • Development process – (Video) 2 min
  • Computation and storage – (Video) 4 min
  • Intro to Qwiklabs – (Video) 5 min
  • Lab debrief – (Video) 11 min
  • Cloud shell – (Video) 2 min
  • Third Wave of Cloud: Fully-Managed Services – (Video) 1 min
  • Third Wave of Cloud: Serverless Data Analysis – (Video) 2 min
  • Third Wave of Cloud: BigQuery and Cloud DataLab – (Video) 52 sec
  • Lab Intro: Analyzing data using AI Platform Notebooks and BigQuery – (Video) 1 min
  • Lab Debrief: Analyzing Data using AI Platform Notebooks and BigQuery – (Video) 7 min
  • Machine Learning, not rules – (Video) 2 min
  • Vision API in action – (Video) 3 min
  • Video intelligence API – (Video) 3 min
  • Cloud Speech API – (Video) 3 min
  • Translation and NL – (Video) 4 min
  • Lab: Pretrained ML APIs Intro – (Video) 43 sec
  • Lab Solution – (Video) 7 min
  • AI Platform Notebooks – (Video) 10 min
  • Intro to Renting-VM Lab – (Video) 10 min
  • Module 5 Quiz – 6 min

Summary: How Google does Machine Learning

Review the core ML topics that this specialization will cover.

  • Summary: ML Strategy – (Video) 4 min

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