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Darren Cook

In this course, we will learn all the core techniques needed to make effective use of H2O. Even if you have no prior experience of machine learning, even if your math is weak, by the end of this course you will be able to make machine learning models using a variety of algorithms. We will be using linear models, random forest, GBMs and of course deep learning, as well as some unsupervised learning algorithms. You will also be able to evaluate your models and choose the best model to suit not just your data but the other business restraints you may be under.

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What's inside

Syllabus

H2O AND THE FUNDAMENTALS
Trees And Overfitting
LINEAR MODELS AND MORE
Read more
Deep Learning
UNSUPERVISED LEARNING
Everything Else!

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Taught by Darren Cook, an instructor with a successful track record of teaching machine learning
Covers core machine learning concepts, including linear models, random forest, and deep learning, making it suitable for beginners with no prior machine learning knowledge
Emphasizes practical applications and enables learners to evaluate and select models based on data and business constraints
Utilizes H2O, an open-source machine learning platform, providing learners with hands-on experience with industry-standard tools
Covers unsupervised learning algorithms, expanding the scope of machine learning techniques taught

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Reviews summary

H2o automl course

learners say this course uses H2o's version of AutoML to teach learners how to create high accuracy machine learning models quickly and easily. Even though the tests and assignments are challenging, students say this course is informative and that it helped improve their programming skills.
Course helps improve programming skills.
"The course not only helped understand various machine learning models but also improved my programming skills."
Creating machine learning models with AutoML is quick and easy.
"You can make high accuracy models quickly and easily with H2O."
Course teaches learners how to use H2O's version of AutoML.
"Teaches one of the quickest ways to get Machine Learning through H2O's version of AutoML."
Course covers a lot of important topics in machine learning.
"The course was very informative and covered a lot of important topics."
Tests and peer graded assignments are challenging.
"Even the tests and peer graded assignments were not simple and direct."

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 Practical Machine Learning on H2O with these activities:
Follow 'A Comprehensive Guide to H2O'
Helps familiarize yourself with H2O, the platform used in this course.
Browse courses on H2O
Show steps
  • Visita the H2O website and create an account.
  • Access the 'A Comprehensive Guide to H2O' tutorial.
  • Work through the tutorial, completing the interactive exercises.
Read 'Machine Learning Yearning'
Provides a solid foundation in machine learning concepts, setting you up for success in this course.
Show steps
  • Obtain a copy of 'Machine Learning Yearning'.
  • Read the first three chapters to get an overview of machine learning.
  • Complete exercises and review questions within the book.
Create a Course Knowledge Base
Supports effective review and knowledge retention throughout the course.
Browse courses on Machine Learning
Show steps
  • Organize course notes, assignments, and other materials in one central location.
  • Review and summarize key concepts regularly.
  • Create flashcards or a study guide for quick reference.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a Study Group
Provides opportunities for collaboration and peer support, enhancing your learning experience.
Browse courses on Machine Learning
Show steps
  • Find or create a study group with fellow course participants.
  • Meet regularly to discuss course material, work on assignments, and share insights.
  • Provide feedback and support to group members.
Complete H2O Practice Drills
Provides hands-on practice with H2O, reinforcing your understanding of its features.
Browse courses on H2O
Show steps
  • Access the H2O practice drills on the course website.
  • Complete at least 10 practice drills, covering different H2O functions and algorithms.
  • Review your results and identify areas for improvement.
Build a Personal Machine Learning Model
Develops your practical skills in applying H2O for real-world machine learning problems.
Browse courses on Machine Learning
Show steps
  • Identify a problem that can be solved using machine learning.
  • Collect and prepare a dataset relevant to the problem.
  • Use H2O to build and train a machine learning model.
  • Evaluate the model's performance and make adjustments as needed.
  • Create a report or presentation summarizing your project.
Participate in the H2O Kaggle Competition
Challenges you to apply your H2O skills in a competitive setting, fostering a deeper understanding.
Browse courses on Machine Learning
Show steps
  • Join the H2O Kaggle Competition.
  • Analyze the competition data and develop a machine learning approach.
  • Build and train your model using H2O.
  • Submit your predictions to the competition leaderboard.
  • Track your progress and learn from other participants.

Career center

Learners who complete Practical Machine Learning on H2O will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
As a Machine Learning Engineer, you will use the principles, algorithms, and techniques of machine learning to build and deploy models that will enhance the ML efforts and help optimize performance. This course is in line with giving you a foundational background in ML. The course will help you explore machine learning, create different models, and evaluate them in order to settle for the best model.
Data Scientist
Data scientists are problem-solvers who use their knowledge of statistics and machine learning to analyze data and extract valuable insights. In this course, you'll learn how to use H2O, an open-source machine learning platform, to build and deploy machine learning models. This will give you the skills you need to succeed as a data scientist.
Quantitative Analyst
Quantitative analysts use mathematical and statistical models to assess the risk of investments. This course will help you build the skills you need to succeed as a quantitative analyst. You'll learn how to use H2O to build and deploy machine learning models, which can be used to analyze financial data and make investment decisions.
Business Analyst
Business analysts use data to solve business problems. This course will help you build the skills you need to succeed as a business analyst. You'll learn how to use H2O to build and deploy machine learning models, which can be used to analyze business data and make better decisions.
Actuary
Actuaries use mathematical and statistical models to assess the risk of future events. This course will help you build the skills you need to succeed as an actuary. You'll learn how to use H2O to build and deploy machine learning models, which can be used to analyze insurance data and make risk assessments.
Software Engineer
Software engineers design, develop, and maintain software systems. This course will help you build the skills you need to succeed as a software engineer. You'll learn how to use H2O to build and deploy machine learning models, which can be used to improve the performance of software systems.
Data Engineer
Data engineers design, build, and maintain data pipelines. This course will help you build the skills you need to succeed as a data engineer. You'll learn how to use H2O to build and deploy machine learning models, which can be used to improve the quality of data pipelines.
Product Manager
Product managers are responsible for the development and launch of new products. This course will help you build the skills you need to succeed as a product manager. You'll learn how to use H2O to build and deploy machine learning models, which can be used to improve the performance of new products.
Marketing Manager
Marketing managers are responsible for the development and execution of marketing campaigns. This course will help you build the skills you need to succeed as a marketing manager. You'll learn how to use H2O to build and deploy machine learning models, which can be used to improve the effectiveness of marketing campaigns.
Sales Manager
Sales managers are responsible for the development and execution of sales strategies. This course will help you build the skills you need to succeed as a sales manager. You'll learn how to use H2O to build and deploy machine learning models, which can be used to improve the performance of sales teams.
Customer Success Manager
Customer success managers are responsible for the satisfaction and retention of customers. This course will help you build the skills you need to succeed as a customer success manager. You'll learn how to use H2O to build and deploy machine learning models, which can be used to improve the customer experience.
Operations Manager
Operations managers are responsible for the day-to-day operations of a business. This course will help you build the skills you need to succeed as an operations manager. You'll learn how to use H2O to build and deploy machine learning models, which can be used to improve the efficiency and effectiveness of operations.
Financial Analyst
Financial analysts provide financial advice to individuals and businesses. This course will help you build the skills you need to succeed as a financial analyst. You'll learn how to use H2O to build and deploy machine learning models, which can be used to analyze financial data and make investment decisions.
Risk Manager
Risk managers are responsible for identifying and managing risks. This course will help you build the skills you need to succeed as a risk manager. You'll learn how to use H2O to build and deploy machine learning models, which can be used to analyze risk data and make risk management decisions.
Insurance Underwriter
Insurance underwriters assess the risk of insurance policies. This course will help you build the skills you need to succeed as an insurance underwriter. You'll learn how to use H2O to build and deploy machine learning models, which can be used to analyze insurance data and make underwriting decisions.

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Practical Machine Learning on H2O.
Practical guide to machine learning with H2O. If you want to learn how to use H2O to solve machine learning problems, this book good option.
Comprehensive textbook on machine learning in Chinese. If you are a Chinese speaker and want to learn about machine learning, this book good option.
A comprehensive and authoritative reference for learning deep learning techniques. This must-read for anyone who wants to learn about deep learning.
A comprehensive textbook on pattern recognition and machine learning. If you want to learn about pattern recognition and machine learning, this book good option.
A comprehensive textbook on machine learning from a probabilistic perspective. If you want to learn about machine learning from a probabilistic perspective, this book good option.
A practical guide to deep learning with Python. The book is written by the creator of Keras, a popular deep learning library. If you want to learn how to use Keras, this book good option.
An advanced textbook that provides a comprehensive overview of statistical learning methods. If you want to learn more about the fundamentals of statistical learning, this book great option.
A comprehensive textbook on data mining techniques. If you want to learn about data mining techniques, this book good option.
A practical guide to machine learning for business professionals. If you are interested in using machine learning to solve business problems, this book good option.
A practical guide to machine learning for finance professionals. If you are interested in using machine learning to solve financial problems, this book good option.
A practical guide to machine learning for healthcare professionals. If you are interested in using machine learning to solve healthcare problems, this book good option.
An introduction to machine learning for non-technical readers. If you are new to machine learning, this book good place to start.

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