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Online Course

Machine Learning Fundamentals

University of California, San Diego via edX

(3)
147
Found in Machine Learning, Artificial Intelligence, Supervised Learning
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  • Provider edX
  • Cost Free Online Course (Audit)
  • Session Upcoming
  • Language English
  • Effort 8-10 hours a week
  • Duration 10 weeks long
  • Learn more about MOOCs

Taken this course? Share your experience with other students. Write review

Overview

Do you want to build systems that learn from experience? Or exploit data to create simple predictive models of the world?

In this course, part of the Data Science MicroMasters program, you will learn a variety of supervised and unsupervised learning algorithms, and the theory behind those algorithms.

Using real-world case studies, you will learn how to classify images, identify salient topics in a corpus of documents, partition people according to personality profiles, and automatically capture the semantic structure of words and use it to categorize documents.

Armed with the knowledge from this course, you will be able to analyze many different types of data and to build descriptive and predictive models.

All programming examples and assignments will be in Python, using Jupyter notebooks.

Taught by

Sanjoy Dasgupta

Tags

machine learning core

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Reviews for edX's Machine Learning Fundamentals Based on 3 reviews

  • 5 stars 67%
  • 4 star 0%
  • 3 star 33%
  • 2 star 0%
  • 1 star 0%

Did you take this course? Share your experience with other students.

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  • 1
Anonymous
Anonymous completed this course.
This is the second course from UCSanDiegoX (early 2018 run) that breaks the enrollment clause stating "Audit this course for free and have complete access to all the course material, activities, tests, and forums". There was no final exam for Audit students. Hopefully this will get corrected in the future runs of this course. The presence of staff on the Audit mode forum is very scarce, and the forums are divided into Verified/Audit students.

The course provides the "fundamentals" in only first few chapters. The more the courses advances the less mathematics is presented which ham…
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ÖY
ömer Y
by ömer is taking this course right now.
I think this course is one of most usefull machine learning courses at internet . Teacher is really good , there are enough math and code exercises
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Luiz C
Luiz completed this course, spending 3 hours a week on it and found the course difficulty to be medium.
I agree with others positive comments regarding this course. I have taken a few popular ML courses. This is probably the best one:

Instructor is top notch, good material, good videos and very clear explanations.

There are lots of exercises.

The only small objection is regarding the python notebooks and the related exercises: the notebooks quaility could have been better (wonder if the person that wrote them has any good CS experience); and the notebook question/exercises could have been better: either too easy, or requiring a touch too much unguided dev: would have enjoyed it more if it was more like in Andrew Ng notebooks in his popular Machine Learning MOOC.

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