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Support Vector Machines in Python – SVM in Python Course Catalog

Support Vector Machines in Python - SVM in Python Course Catalog Learn Support Vector Machines in Python. Covers basic SVM models to Kernel-based advanced SVM models of Machine Learning
Support Vector Machines in Python - SVM in Python Course Catalog Learn Support Vector Machines in Python. Covers basic SVM models to Kernel-based advanced SVM models of Machine Learning

Support Vector Machines in Python – SVM in Python Course Catalog

Learn Support Vector Machines in Python. Covers basic SVM models to Kernel-based advanced SVM models of Machine Learning

What you’ll learn

Support Vector Machines in Python – SVM in Python Course Catalog

  • Get a solid understanding of Support Vector Machines (SVM)
  • Understand the business scenarios where Support Vector Machines (SVM) is applicable
  • Tune a machine learning model’s hyperparameters and evaluate its performance.
  • Use Support Vector Machines (SVM) to make predictions
  • Implementation of SVM models in Python

Requirements

  • Students will need to install Python and Anaconda software but we have a separate lecture to help you install the same

Description

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?

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 techniques of machine learning, which is 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 a 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 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:

This is very good, I love the fact the all explanation given can be understood by a layman – Joshua

Thank you, Author, for this wonderful course. You are the best and this course is worth any price. – Daisy

Our Promise

Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.

Download Practice files take Quizzes and complete Assignments

With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning.

Go ahead and click the enroll button, and I’ll see you in lesson 1!

Cheers

Start-Tech Academy

Who this course is for:

Support Vector Machines in Python – SVM in Python Course Catalog

Download Now Content From: https://www.udemy.com/course/machine-learning-adv-support-vector-machines-svm-python/

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