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.
Practical Machine Learning on H2O
Gain insight into a topic and learn the fundamentals.
74 reviews
Intermediate level
Some related experience required
3 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Skills you'll gain
- Autoencoders
- Predictive Modeling
- Decision Tree Learning
- Data Preprocessing
- Classification Algorithms
- Data Manipulation
- Random Forest Algorithm
- Feature Engineering
- Unsupervised Learning
- Applied Machine Learning
- Supervised Learning
- Dimensionality Reduction
- Machine Learning
- Model Evaluation
- Deep Learning
- Anomaly Detection
Details to know
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Taught in English
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There are 6 modules in this course
What's included
11 videos4 readings5 assignments
What's included
15 videos1 reading3 assignments1 peer review
What's included
9 videos4 readings3 assignments
What's included
11 videos2 readings5 assignments1 peer review
What's included
10 videos2 readings3 assignments
What's included
9 videos2 readings1 assignment1 peer review
Instructor
Instructor ratings
(10 ratings)
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Showing 3 of 74
RM
Reviewed on Sep 30, 2019
awsome but needs more to explain on autoencoder ,anomely
KD
Reviewed on Oct 12, 2019
One of the best courses regarding machine learning!
MP
Reviewed on Aug 10, 2019
It was a great experience to work with H2O both on R as well as Python.I learned a lot from the course.
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