FA18
Machine Learning
Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. This area is also concerned with issues both theoretical and practical.
In this course, we will present algorithms and approaches in such a way that grounds them in larger systems as you learn about a variety of topics, including:
- statistical supervised and unsupervised learning methods
- randomized search algorithms
- Bayesian learning methods
- reinforcement learning
The course also covers theoretical concepts such as inductive bias, the PAC and Mistake‐bound learning frameworks, minimum description length principle, and Ockham's Razor. In order to ground these methods the course includes some programming and involvement in a number of projects.
By the end of this course, you should have a strong understanding of machine learning so that you can pursue any further and more advanced learning.
This is a three-credit course.
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| Rating | 3.7★ based on 9 ratings |
|---|---|
| Length | 14 weeks |
| Effort | 8 - 10 hours per week |
| Starts | Aug 20 (300 weeks ago) |
| Cost | $99 |
| From | The Georgia Institute of Technology, GTx via edX |
| Instructors | Charles Isbell Jr., Charles Isbell |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Analysis & Statistics |
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What people are saying
assignments lack mathematical/programming rigor
The only downside is that weekly assignments lack mathematical/programming rigor which can be improved in future sessions.
become an incredibly useful
Provided these prerequisites are available (anyone who is serious about the field should possess these skills anyway), the course will become an incredibly useful resource to break into Machine Learning.
give an opportunity implement
There are four programming assignments which give an opportunity implement some of the algorithms learned.
pass with minimal effort
It is not like many other courses that you can take and pass with minimal effort but at the end of it, it is worth spending time taking this course.
possess these skills anyway
worth spending time taking
breaks down hard concepts
Professor Paisley covers a whole range of topics and breaks down hard concepts clearly.
enough on geometric interpretation
In general, too much emphasis on algebra, and not enough on geometric interpretation of algebra and solutions.
requires a solid foundation
This course requires a solid foundation on probabilities, calculus, linear algebra and programming.
overall must do
Overall must do course for anyone interested in this topic.
field should possess
too much emphasis
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
Research Scientist-Machine Learning $55k
Cloud Architect - Azure / Machine Learning $75k
Watson Machine Learning Engineer $81k
Machine Learning Software Developer $103k
Software Engineer (Machine Learning) $116k
Applied Scientist, Machine Learning $130k
Autonomy and Machine Learning Solutions Architect $131k
Applied Scientist - Machine Learning -... $136k
RESEARCH SCIENTIST (MACHINE LEARNING) $147k
Machine Learning Engineer 2 $161k
Machine Learning Scientist Manager $170k
Machine Learning Scientist, Personalization $213k
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| Rating | 3.7★ based on 9 ratings |
|---|---|
| Length | 14 weeks |
| Effort | 8 - 10 hours per week |
| Starts | Aug 20 (300 weeks ago) |
| Cost | $99 |
| From | The Georgia Institute of Technology, GTx via edX |
| Instructors | Charles Isbell Jr., Charles Isbell |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Analysis & Statistics |
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