Unsupervised Machine Learning Hidden Markov Models in Python
What you’ll learn
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Understand and enumerate the various applications of Markov Models and Hidden Markov Models
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Understand how Markov Models work
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Write a Markov Model in code
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Apply Markov Models to any sequence of data
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Understand the mathematics behind Markov chains
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Apply Markov models to language
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Apply Markov models to website analytics
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Understand how Google’s PageRank works
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Understand Hidden Markov Models
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Write a Hidden Markov Model in Code
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Write a Hidden Markov Model using Theano
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Understand how gradient descent, which is normally used in deep learning, can be used for HMMs
Who this course is for:
- Students and professionals who do data analysis, especially on sequence data
- Professionals who want to optimize their website experience
- Students who want to strengthen their machine learning knowledge and practical skillset
- Students and professionals interested in DNA analysis and gene expression
- Students and professionals interested in modeling language and generating text from a model
Can I download Unsupervised Machine Learning Hidden Markov Models in Python course?
You can download videos for offline viewing in the Android/iOS app. When course instructors enable the downloading feature for lectures of the course, then it can be downloaded for offline viewing on a desktop.Can I get a certificate after completing the course?
Yes, upon successful completion of the course, learners will get the course e-Certification from the course provider. The Unsupervised Machine Learning Hidden Markov Models in Python course certification is a proof that you completed and passed the course. You can download it, attach it to your resume, share it through social media.Are there any other coupons available for this course?
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Disclosure: This post may contain affiliate links and we may get small commission if you make a purchase. Read more about Affiliate disclosure here.
