Machine Learning Terminology & Process For Beginners - ClayDesk

Machine Learning Terminology & Process For Beginners

Machine Learning Terminology & Process For Beginners

Categories: Business, Design, IT & Software
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About Course

Welcome to Machine Learning Terminology course.

Are you new to machine learning? Are you looking to enhance you skills within the AWS ecosystem or perhaps pursue AWS certifications?Look no further – learn and acquire new skills with this Machine Learning Terminology course.

Course Description

Welcome to Machine Learning Terminology course – A one of its kind course for beginners! In other words, it is not only a comprehensive course, but you will not find a course similar to this. 

Note: AWS Machine learning is not free. Therefore, please note that you may incur additional costs from AWS.

In this course, you’ll learn and practice, for instance:
  1. Basic machine learning terminology and process
  2. Similarly, learn how to frame a machine learning problem and when to use machine learning
  3. Prepare and develop data sets. In addition, gain solid understanding of feature engineering and data visualizations
  4. Work with model training and evaluation
  5. Learn about business goal evaluation
  6. See machine learning prediction, and much more….  

Above all, in this course, you will also get complete resources, and code where applicable with this course! We’ve built this course with our Team ClayDesk of industry recognized developers and consultants to bring you the best of everything!

What out students say…

See what our students say “It is such a comprehensive course. Moreover, I don’t need to take any other course but this one to learn all of Machine Learning processes and important terminology along with demos – Absolutely worth it” – Chavez

“This is such an awesome course. In other words, I loved every bit of it – Wonderful learning experience!”  Jill Neumann.

Why take this course?

I am a senior Project Manager & Web developer, managing and deploying enterprise level IT projects. In addition, I am also a Microsoft Certified Systems Engineer & Trainer, and have been working on Machine Learning projects. Therefore, I am excited to share my knowledge and transfer skills to my students. 

In conclusion, enroll now in Machine Learning Terminology & Process For Beginners today and revolutionize your learning. Stay at the cutting edge of enterprise cloud computing — and enjoy bigger, brighter opportunities.

In addition to the ClayDesk E-Campus 30-day money back guarantee, you have my personal guarantee. Moreover, you will love what you learn in this course. However, if you ever have any questions please feel free to message us directly and we will do our best to get back to you as soon as possible! You will also get FREE web hosting at ClayDesk hosting service once you enroll. Subscribe to our YouTube Channel for additional resources.

See you in class!

Syed & Team ClayDesk

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What Will You Learn?

  • Fundamentals of Machine Learning Terminology
  • Learn how to frame a machine learning problem
  • Prepare and develop machine learning data sets
  • Work with model training and evaluation
  • Learn about business goal evaluation
  • Use Python in AWS Rekognition

Course Content

Introduction
Introduction

Machine Learning Problem Framing
In this section you will learn how to frame a machine learning problem in detail

Working With DataSets
In this section you will explore and learn about data sets. For example, you will learn how to prepare raw data to be used with machine learning

Data Visualization & Feature Engineering
In this section you will learn about how to visualize your data and use feature engineering with given data sets

Model Training & Evaluation
In this section you will learn about training your machine learning model and finally evaluating your machine learning model

Business Goal Evaluation
In this section you will learn how to evaluate your business or organizational goals and objectives before prediction

Machine Learning In Action Demo
Machine Learning In Action

Conclusion & Bonus
In this section you will find bonus lectures and valuable resources