Description
Cluster Analysis and Unsupervised Machine Learning in Python is the name of the training course on cluster analysis and unsupervised machine learning in Python, published by the Udemy website. Cluster analysis is one of the main foundations of unsupervised machine learning and data science.
Is. which is very useful for data mining and big data because, unlike supervised machine learning, it automatically finds patterns in data, without the need for threading. In the real world, imagine that a robot or an AI will not always have access to the optimal answer, or that there may not be an optimal correct answer. You want that robot to be able to explore the world on its own and learn things just by looking for patterns.
Have you ever wondered how we get the data we use in our supervised machine learning algorithms? We always seem to have a nice CSV or table populated with the corresponding X’s and Y’s. This data has to come from somewhere, and in many cases it is collected traditionally. Sometimes, you do not have access to this type of information or it is impossible or expensive to obtain it. But you still want to have some idea of the data structure. If you do data analysis, automatic pattern recognition in your data will be invaluable. This is where unsupervised machine learning comes into play.
What you will learn in the course Cluster Analysis and Unsupervised Machine Learning in Python:
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Understand regularized K-Means algorithm
- Understand the K-Means Clustering algorithm in soft or fuzzy modes
- Understand hierarchical clustering
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Apply the Scipy Hierarchical Clustering library to the data
- Learn about the Gaussian mixture model and how to use it to estimate density
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Explain when GMM is equivalent to K-Means Clustering
- Understand how GMM overcomes some of the disadvantages of K-Means
Course details
Publisher: Udemy
Instructor: Lazy Programmer Team, Lazy Programmer Inc
English language
Education level: introductory
Number of courses: 56
Training duration: 8 hours
The headings of the course Cluster Analysis and Unsupervised Machine Learning in Python:
Course prerequisites:
- Know how to code in Python and Numpy
- Install Numpy and Scipy
- Matrix arithmetic, probability
Course pictures:
Installation guide
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English subtitle
Quality: 720p
download link
Download part 1 – 1 GB
Download part 2 – 400 MB
file password link
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