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.
oferecido por
Practical Machine Learning on H2O
H2OInformações sobre o curso
17,490 visualizações recentes
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 19 horas para completar
Inglês
Legendas: Inglês
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 19 horas para completar
Inglês
Legendas: Inglês
Programa - O que você aprenderá com este curso
2 horas para concluir
H2O AND THE FUNDAMENTALS
2 horas para concluir
11 vídeos (Total 64 mín.), 4 leituras, 5 testes
11 videos
Welcome!2min
What's In Week One?2min
Need To Know5min
Preinstall #1 (with Linux)7min
Preinstall #2 (with Windows)4min
Installing H2O4min
A Quick Deep Learning!19min
AutoML6min
Types Of Models7min
Where To Go With Questions2min
Summary1min
4 leituras
Further Reading: Course Prerequisites10min
Pre-Install Summary10min
Additional Install Information10min
Further Reading: Getting Help10min
5 exercícios práticos
Do You Have What It Takes?10min
Quick Preinstall Check6min
Quick Install Check4min
Model types4min
Week One Exam14min
4 horas para concluir
Trees And Overfitting
4 horas para concluir
15 vídeos (Total 57 mín.), 1 leitura, 4 testes
15 videos
Weekly Intro1min
Decision Trees3min
Random Forest2min
Random Forest in H2O (Iris)4min
GBM2min
GBM in H2O (Iris)3min
Importing From Client4min
Artificial Data Sets6min
Overfitting and Train/Valid/Test4min
Train/Valid/Test in H2O3min
GBM in H2O (artificial data)4min
Let's Overfit A GBM!4min
Cross-validation in H2O (GBM)7min
About the peer review task3min
Week Two Summary44s
1 leituras
Further Reading: Tree Algorithms10min
3 exercícios práticos
Decision Trees4min
Tree Algorithms8min
On cross-validation and over-fitting18min
2 horas para concluir
LINEAR MODELS AND MORE
2 horas para concluir
9 vídeos (Total 56 mín.), 4 leituras, 3 testes
9 videos
Loading From Remote Sources6min
Exporting Data From H2O2min
Exploring With GLMs11min
Naive Bayes4min
Data Manipulation, Statistics11min
Grid Search8min
Applying Grids8min
Summary50s
4 leituras
More on loading and saving10min
Further Reading: GLMs, Naive Bayes10min
Further Reading: Data Manipulation10min
Further Reading: Grid Search10min
3 exercícios práticos
Load/Save4min
GLMs6min
Week Three Exam16min
4 horas para concluir
Deep Learning
4 horas para concluir
11 vídeos (Total 66 mín.), 2 leituras, 6 testes
11 videos
Load & Save Models1min
Binding data tables6min
Merging and joins3min
Neural Networks6min
Deep Learning Part 19min
Deep Learning Part 210min
Deep Learning with Grids11min
Regression with Deep Learning7min
Introducing The Graded Task3min
Summary Of Week Four1min
2 leituras
More Neural Net Theory10min
Extension Project Ideas10min
5 exercícios práticos
Early Stopping6min
Binding4min
Merging4min
Deep Learning Basics6min
More Deep Learning4min
Avaliações
Principais avaliações do PRACTICAL MACHINE LEARNING ON H2O
por RE10 de Set de 2018
I've taken a lot of Coursera classes and this is one of the better classes. It is a good hands-on course and will help students learn more about not only H2O, but also machine learning.
por EA3 de Fev de 2019
Great content, a lot of hands-on activities and the instructor is quite good too. By the end of the course, I feel that I have the necessary skills to work with h2o.
por MP10 de Ago de 2019
It was a great experience to work with H2O both on R as well as Python. I learned a lot from the course.
por RM30 de Set de 2019
awsome but needs more to explain on autoencoder ,anomely
Perguntas Frequentes – FAQ
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.
Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.
© 2020 Coursera Inc. Todos os direitos reservados.
