Evaluating the Performance of Clusters

Content Provider

Packt Admin

Duration

5 Min

Mode Of Delivery

Online

Course Validity

12 months

Course Level

Advanced

Certification By

Go1 - KRACKiN
  • ( ₹9999 ₹3499)
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Description

You'll begin by learning how to use the syntax of scikit-learn. You'll study the difference between supervised and unsupervised models, as well as the importance of choosing the appropriate algorithm for each dataset. You'll apply unsupervised clustering algorithm over 1990 US Census dataset, to discover patterns and profiles, and explore the process to solve a supervised machine learning problem. Then, the focus of the course shifts to supervised learning algorithms.



You'll learn to implement different supervised algorithms and develop neural network structures using the scikit-learn package. You'll also learn how to perform coherent result analysis to improve performance of the algorithm by tuning hyperparameters. When it finishes, this course would have given you the skills and confidence to start programming machine learning algorithms.



 



Target Audience



Machine Learning Fundamentals is designed for developers who are new to the field of machine learning and want to learn how to use the scikit-learn library to develop machine learning algorithms. You must have some knowledge and experience in Python programming, but you do not need any prior knowledge of scikit-learn or machine learning algorithms.


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