Machine Learning Fundamentals
- Provider edX
- Cost Free Online Course (Audit)
- Session Upcoming
- Language English
- Effort 8-10 hours a week
- Duration 10 weeks long
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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.
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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%
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The course provides the "fundamentals" in only first few chapters. The more the courses advances the less mathematics is presented which ham…
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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