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Coupon & course info

Course Name: Unsupervised Machine Learning Hidden Markov Models in Python

Subtitle: HMMs for stock price analysis, language modeling, web analytics, biology, and PageRank.

Instructor: Taught by Justin C, Data scientist and big data engineer

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $120 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of September 8, 2016…

Students: 614 students enrolled

Ratings: 51 reviews

Rank: ranked #73d in Udemy Business Courses

Brief course description

The Hidden Markov Model or HMM is all about learning sequences.

A lot of the data that would be very useful for us to model is in sequences. Stock prices are sequences of prices. Language is a sequence of words. Credit scoring involves sequences of borrowing and repaying money, and we can use those sequences to predict whether or not you’re going to default. In short, sequences are everywhere, and being able to analyze them is an important skill in your data science toolbox.

The easiest way to appreciate the kind of information you get from a sequence is to consider what you are reading right now. If I had written the previous sentence backwards, it wouldn’t make much sense to you, even though it contained all the same words. So order is important.

(Read more about this course on the official course page.)

Justin C bio

I am a data scientist, big data engineer, and full stack software engineer.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 40 lessons

Duration: 4.5 hours of video

What you get: Understand and enumerate the various applications of Markov Models and Hidden Markov Models

Target audience: Students and professionals who do data analysis, especially on sequence data

Requirements: Familiarity with probability and statistics

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons