Improve business outcomes with ML & AI
With the adoption of Machine Learning you will develop robust models for analyzing bigger and more complex data and identify opportunities and potential risks. This course provides a foundation of the two largest areas in machine learning: supervised and unsupervised learning.
You will learn how machine learning techniques are applied to business problems, as well as how to implement these techniques using popular Python libraries. In addition, you will gain experience in extracting useful information and identify patterns in the data.
Understand the fundamentals concepts of machine learning and its challenges
Know of the strengths and weaknesses of many popular machine learning approaches
Design and implement various machine learning algorithms for different types of problems
Machine Learning Fundamentals
DAY 1
Optimization Methods
DAY 2
Classification I
DAY 3
Classification II - Ensemble Methods
DAY 4
Launch your career in Data Science
Next Bootcamp: September 25 - December 18
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