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Machine Learning for Business Professionals from Google

Machine learning is the study of algorithms and mathematical models that computer systems use to progressively improve their performance on a specific task. Machine learning algorithms build a mathematical model of sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task.The types of machine learning algorithms differ in their approach, the type of data they input and output, and the type of task or problem that they are intended to solve.Supervised learning algorithms build a mathematical model of a set of data that contains both the inputs and the desired outputs.Unsupervised learning algorithms take a set of data that contains only inputs, and find structure in the data, like grouping or clustering of data points. The algorithms therefore learn from test data that has not been labeled, classified or categorized.

Ninety percent of all the world’s data has been created in the last two years. Business around the world generate approximately 450 billion transactions a day. The amount of data collected by all organizations is approximately 2.5 exabytes a day. That number doubles every month.That means,there is always exponential need for Machine learning engineers to build, implement, and maintain machine learning systems,algorithms in technology products with focus on machine learning system reliability, performance, and scalability.

In this post,we check out new course from Google,this course is intended to be an introduction to machine learning for non-technical business professionals.

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Machine Learning for Business Professionals

By the end of this course, you will have learned how to:

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  • Formulate machine learning solutions to real-world problems
  • Identify whether the data you have is sufficient for ML
  • Carry a project through various ML phases including training, evaluation, and deployment
  • Perform AI responsibly and avoid reinforcing existing bias
  • Discover ML use cases
  • Be successful at ML

You’ll need a desktop web browser to run this course’s interactive labs via Qwiklabs and Google Cloud Platform.

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What you will learn from this course

#1.Introduction

This module reviews the learning objectives for the course and introduces technology that will be important for completing labs.

#2.What is Machine Learning?

This module defines what machine learning is, provides examples of how businesses are using it, contextualizes recent advances in machine learning, and reviews how artificial intelligence raises important ethical questions.

#3.Employing ML

This module reviews how to do machine learning, including how to label data, train and evaluate models and avoid reinforcing bias.

#4.Discovering ML Use Cases

This module reviews broad categories of ML use cases in order to jump start your ideation.

#5.How to be successful at ML

This module reviews what your business must do in order to be successful at ML, including how to acquire data, how to appropriately govern that data, and how to create a culture of innovation.
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Machine Learning for Business Professionals from Google
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Machine Learning for Business Professionals from Google
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In this post,we take look at course from Google on Machine learning for non-technical business professionals.
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Upnxtblog
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