Introduction to Machine Learning
Want to learn how to analyze the huge amounts of data? In this course you will learn modern methods of machine learning to help you choose the right methods to analyze your data and interpret the results correctly.
This course is an introduction to machine learning. It will cover the modern methods of statistics and machine learning as well as mathematical prerequisites for them. We will discuss the methods used in classification and clustering problems. You will learn different regression methods.
Various examples and different software applications are considered in the course. You will get not only the theoretical prerequisites, but also practical hints on how to work with your data in MS Azure.
What you'll learn
- Introduction to machine learning and mathematical prerequisites
- Regression types (linear, polynomial, multi variable regression)
- Classification methods: Logistic regression, Naïve Bayes and K-nearest neighbours
- Clustering methods: hierarchical and k-means clustering
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| Rating | Not enough ratings |
|---|---|
| Length | 5 weeks |
| Effort | 2 - 4 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $149 |
| From | ITMOx, ITMO University via edX |
| Instructors | Anton Boitsev, Aleksei Romanov, Dmitry Volchek, Elena Mikhailova, Natalia Grafeeva, Olga Egorova |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Analysis & Statistics |
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| Rating | Not enough ratings |
|---|---|
| Length | 5 weeks |
| Effort | 2 - 4 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $149 |
| From | ITMOx, ITMO University via edX |
| Instructors | Anton Boitsev, Aleksei Romanov, Dmitry Volchek, Elena Mikhailova, Natalia Grafeeva, Olga Egorova |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Analysis & Statistics |
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