Creating Machine Learning Models from Pluralsight

This course covers the important types of machine learning algorithms, solution techniques based on the specifics of the problem you are trying to solve, as well as the classic machine learning workflow.

As Machine Learning explodes in popularity, it is becoming ever more important to know precisely how to frame a machine learning model in a manner appropriate to the problem we are trying to solve, and the data that we have available.

In this course, Creating Machine Learning Models you will gain the ability to choose the right type of model for your problem, then build that model, and evaluate its performance.

First, you will learn how rule-based and ML-based systems differ and their strengths and weaknesses and how supervised and unsupervised learning models differ from each other.

Next, you will discover how to implement a range of techniques to solve the supervised learning problems of classification and regression. You will gain an intuitive understanding of the the model algorithms you can use for classification and regression. Finally, you will round out your knowledge by building clustering models using a couple of different algorithms, and validating the results.

When you’re finished with this course, you will have the skills and knowledge to identify the correct machine learning problem setup, and the appropriate solution and evaluation techniques for your use-case.

What's inside

Syllabus

Course Overview

Understanding Approaches to Machine Learning

Understanding and Implementing Regression Models

Understanding and Implementing Classification Models

Understanding and Implementing Clustering Model

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Helps students understand how to choose the best model for their needs

Covers a range of techniques for solving supervised learning problems

Provides an intuitive understanding of classification and regression model algorithms

Teaches how to build clustering models using different algorithms

Helps students validate the results of their machine learning models

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Creating Machine Learning Models with these activities:

Connect with professionals in the machine learning field

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Expand your professional network and gain insights from other practitioners in the field.

Browse courses on Machine Learning

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Attend industry meetups, conferences, or online forums related to machine learning
Introduce yourself to other attendees

Review machine learning terminology

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Become accustomed to the concepts of Machine Learning models by reviewing related terminology.

Browse courses on Machine Learning

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Review the key terms and concepts of machine learning.
Create flashcards or a glossary of terms.
Practice using the terms in context.

Organize and review learning materials

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Become accustomed to the concepts of Machine Learning models by reviewing course materials.

Browse courses on Machine Learning

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Review the notes and materials from past courses in machine learning
Review foundational statistics
Review previous coding projects you have completed

Five other activities

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Build a simple machine learning model

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Build upon the concepts of supervised machine learning by completing a tutorial on building a simple model.

Browse courses on Machine Learning

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Choose a tutorial for building a simple machine learning model
Follow the steps in the tutorial to build the model.
Test your model with some data.
Evaluate the performance of the machine learning model

Practice implementing common machine learning algorithms

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Practice applying concepts of machine learning algorithms with hands-on exercises.

Browse courses on Machine Learning

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Solve practice problems or coding challenges involving machine learning algorithms
Participate in online coding competitions or hackathons that focus on machine learning

Experiment with different machine learning algorithms for a project

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Apply the knowledge gained through this course in a project that involves experimenting with different machine learning algorithms.

Browse courses on Machine Learning

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Choose a project idea that aligns with your interests and career goals.
Gather the necessary data and resources.
Explore and compare various machine learning algorithms for your project.
Train and evaluate your machine learning models.
Present your findings and discuss the implications of your project.

Attend a workshop on advanced machine learning techniques

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Extend your knowledge further by attending an industry-based machine learning workshop.

Browse courses on Machine Learning

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Identify and register for a relevant workshop on advanced machine learning techniques.
Attend the workshop with a focus on actively learning and engaging in discussions.
Apply the knowledge and insights gained in your future machine learning endeavors.

Mentor or tutor students in Machine Learning topics

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Deepen your understanding of Machine Learning concepts by teaching and assisting others.

Browse courses on Machine Learning

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Identify opportunities to volunteer as a mentor or tutor for students in Machine Learning courses.
Prepare and deliver learning materials, provide guidance, and answer questions for your mentees.

Career center

Learners who complete Creating Machine Learning Models will develop knowledge and skills that may be useful to these careers:

Data Scientist

To be successful as a Data Scientist, one needs to be able to frame machine learning models in a manner appropriate to the problem they are trying to solve, and the data that they have available. This course, Creating Machine Learning Models, can help you develop the skills and knowledge you need to do just that.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers need to be able to implement a range of techniques to solve supervised learning problems of classification and regression. This course can help you gain an understanding of the model algorithms you can use for these tasks.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

Data Analysts need to be able to use machine learning techniques to solve business problems. This course can help you develop the skills you need to do just that by teaching you about the different types of machine learning algorithms and how to implement them.

See salaries and explore the career path for Data Analyst

Software Engineer

Software Engineers who specialize in machine learning need to have a strong foundation in the principles of machine learning. This course can help you build that foundation by teaching you about the important types of machine learning algorithms and the classic machine learning workflow.

See salaries and explore the career path for Software Engineer

Operations Research Analyst

Operations Research Analysts use machine learning techniques to solve business problems. This course can help you develop the skills you need to do just that by teaching you about the different types of machine learning algorithms and how to implement them.

See salaries and explore the career path for Operations Research Analyst

Data Architect

Data Architects who work with machine learning need to have a good understanding of the principles of machine learning. This course can help you build that understanding by teaching you about the different types of machine learning algorithms and the classic machine learning workflow.

See salaries and explore the career path for Data Architect

Database Administrator

Database Administrators who work with machine learning need to have a good understanding of the principles of machine learning. This course can help you build that understanding by teaching you about the different types of machine learning algorithms and the classic machine learning workflow.

See salaries and explore the career path for Database Administrator

Product Manager

Product Managers who work on machine learning products need to have a good understanding of the principles of machine learning. This course can help you build that understanding by teaching you about the different types of machine learning algorithms and the classic machine learning workflow.

See salaries and explore the career path for Product Manager

Quantitative Analyst

Quantitative Analysts use machine learning techniques to analyze data and make predictions. This course can help you develop the skills you need to do just that by teaching you about the different types of machine learning algorithms and how to implement them.

See salaries and explore the career path for Quantitative Analyst

Statistician

Statisticians who work with machine learning need to have a good understanding of the principles of machine learning. This course can help you build that understanding by teaching you about the different types of machine learning algorithms and the classic machine learning workflow.

See salaries and explore the career path for Statistician

Business Analyst

Business Analysts who work with machine learning projects need to have a good understanding of the principles of machine learning. This course can help you build that understanding by teaching you about the different types of machine learning algorithms and the classic machine learning workflow.

See salaries and explore the career path for Business Analyst

Information Scientist

Information Scientists who work with machine learning need to have a good understanding of the principles of machine learning. This course can help you build that understanding by teaching you about the different types of machine learning algorithms and the classic machine learning workflow.

See salaries and explore the career path for Information Scientist

Systems Engineer

Systems Engineers who work with machine learning need to have a good understanding of the principles of machine learning. This course can help you build that understanding by teaching you about the different types of machine learning algorithms and the classic machine learning workflow.

See salaries and explore the career path for Systems Engineer

Computer Scientist

Computer Scientists who work with machine learning need to have a good understanding of the principles of machine learning. This course can help you build that understanding by teaching you about the different types of machine learning algorithms and the classic machine learning workflow.

See salaries and explore the career path for Computer Scientist

Network Engineer

Network Engineers who work with machine learning need to have a good understanding of the principles of machine learning. This course can help you build that understanding by teaching you about the different types of machine learning algorithms and the classic machine learning workflow.

See salaries and explore the career path for Network Engineer