Bert Gollnick
Did you ever wonder how machines learn – in this course you will find out.
We will cover all fields of Machine Learning: Regression and Classification techniques, Clustering, Association Rules, Reinforcement Learning, and, possibly most importantly, Deep Learning for Regression, Classification, Convolutional Neural Networks, Autoencoders, Recurrent Neural Networks, …
For each field, different algorithms are shown in detail: their core concepts are presented in 101 sessions. Here, you will understand how the algorithm works. Then we implement it together in lab sessions. We develop code, before I encourage you to work on exercise on your own, before you watch my solution examples. With this knowledge you can clearly identify a problem at hand and develop a plan of attack to solve it.
You will understand the advantages and disadvantages of different models and when to use which one. Furthermore, you will know how to take your knowledge into the real world.
You will get access to an interactive learning platform that will help you to understand the concepts much better.
In this course code will never come out of thin air via copy/paste. We will develop every important line of code together and I will tell you why and how we implement it.
Instructor Details
Courses : 1
Specification: Machine Learning, incl. Deep Learning, with R
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10 reviews for Machine Learning, incl. Deep Learning, with R
Add a review
| Price | $14.99 |
|---|---|
| Provider | |
| Duration | 15.5 hours |
| Year | 2019 |
| Level | All |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
$14.99
Nikhil Rai –
I think I chose one of the best course.
Jos Antonio Hern ndez Guti rrez –
It is a great course. I am enjoying it. Thanks!
ILYA F. –
Good explanations, solid content.
Balaji –
simple explanation and good overview
Alex Deck –
I am through 25% of the modules, and having a great time. The explanations are clear and effective. I will have to do my own practice on the topics (ideally in a professional setting where I have access to many different sets of data), but just viewing the lectures is a great start. Also, I have very little experience in R. This course alone is a good resource to strengthen my knowledge in R within a useful context.
Kidus Tesera –
Tanxs mate, it’s been nice so far!
Paul Ryder –
Looking good so far.
Richard Ngamita –
Good stuff, so far so good. Learning the basics that i always hear about.
Leona Pais –
The course needs more details and explanation! Would not recommend it at all
Celia Banks –
This course was exactly what I needed to springboard into understanding Deep Learning in Machine Language as both relate to R. Many courses out there align the topics more with Python so the fact that this was geared to R was my attraction to it. Got more than what I bargained for…instructor is well versed in the subject area and his articulation of dense topic areas gave an effortless flow from beginning to end. The breadth of the course curriculum provided insight into the range of areas pertinent to deep learning. Would recommend this course without hesitation to those interested in this topic regardless of experience level none up to intermediate. BTW, I usually withhold my rating till the near end (90% complete), but this course has been reliable section after section. Kudos to great instructional delivery!