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An Introduction To Machine Learning With Cluster Analysis Using Python

An Introduction To Machine Learning With Cluster Analysis Using Python


The second part begins with an introduction of machine learning followed by a comparison of supervised and unsupervised machine leaning concepts.

Overview

Description
The first part of this course deals with the basics of python programming language. The second part begins with an introduction of machine learning followed by a comparison of supervised and unsupervised machine leaning concepts. Cluster analysis is discussed as a category of unsupervised machine learning. Subsequently, it offers an in-depth theoretical knowledge and practical implementation in python code of two most popular clustering algorithms – k-means and Hierarchical clustering. This second part tries to maintain a fine balance between necessary theoretical knowledge needed by a data scientist and practical implementation details using python programming language. The third part of the course consists of practice problem sets where students can put into practice their understanding of python and clustering.

Basic knowledge
No prior knowledge of python is required for this course as the first part of the course deals with the basics of python in enough details

Course Information

No prior knowledge of python is required for this course as the first part of the course deals with the basics of python in enough details

What will you learn
Part I- Python Basics:

Installation and Environments
Variable, Identifier, keywords, and Operators
Control Statements- conditionals, loops
Functions
Modules
Data Structure-List, Tuple, Set, Dictionary
Data Manipulation using Pandas library
Arrays, Linear Algebra, Summary statistics using Numpy library
Data visualization using Matplotlib and Seaborn
Part II – Clustering:

Understanding Machine Learning, supervised and unsupervised learning
Clustering definition and concept
K-means clustering
Hierarchical clustering
Part III – Practice Problem sets

Who this course is for:
Students and professionals interested in machine learning and data science
People who want an introduction to unsupervised machine learning and cluster analysis
People who want to know how to write their own clustering code
Professionals interested in data mining big data sets to look for patterns automatically

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Course Specifications

Find various Data Analyst courses including a diploma in data analytics

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Adult education is the non-credential activity of gaining skills and improved education. 

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Online education is electronically supported learning that relies on the Internet for teacher/student interaction. 

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A short course is a learning programme that gives you combined content or specific skills training in a short period of time. Short courses often lean towards the more practical side of things and have less theory than a university course – this gives you a more hands-on experience within your field of interest.

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Course duration is 24 hours.

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