Support Vector Machines in Python: SVM Concepts & Code

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Support Vector Machines in Python: SVM Concepts & Code

About this course

You're looking for a complete Support Vector Machines course that teaches you everything you need to create a Support Vector Machines model in Python, right?You've found the right Support Vector Machines techniques course!How this course will help you?A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning advanced course.If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the advanced technique of machine learning, which are Support Vector Machines.Why should you choose this course?This course covers all the steps that one should take while solving a business problem through Decision tree.Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business.What makes us qualified to teach you?The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course We are also the creators of some of the most popular online courses - with over 150,000 enrollments and thousands of 5-star reviews like these ones:This is very good, i love the fact the all explanation given can be understood by a layman - JoshuaThank you Author for this wonderful course. You

What you'll learn

  • understanding the principles of Support Vector Machines
  • pre-processing data for machine learning analysis
  • evaluating model performance and interpreting results
  • applying SVM techniques to solve business problems

Course objectives

  • to teach the steps necessary for creating a Support Vector Machine model
  • to emphasize the importance of data preparation and post-analysis evaluation in machine learning

Skills you'll gain

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