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 - Joshua
Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy
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!
- Students will need to install Python and Anaconda software but we have a separate lecture to help you install the same
What you'll learn:
- 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
- 001 Installing Python and Anaconda FREE PREVIEW
- 002 Opening Jupyter Notebook
- Course Resources
- 003 Introduction to Jupyter
- 004 Arithmetic operators in Python Python Basics
- 006 Lists Tuples and Directories Python Basics
- 007 Working with Numpy Library of Python
- 008 Working with Pandas Library of Python
- 005 Strings in Python Python Basics
- 009 Working with Seaborn Library of Python
- 010 Introduction to Machine Learning
- 011 Building a Machine Learning Model
- 012 Course flow
- 013 The Concept of a Hyperplane
- 014 Maximum Margin Classifier
- 015 Limitations of Maximum Margin Classifier
- 016 Support Vector classifiers
- 017 Limitations of Support Vector Classifiers
- 018 Kernel Based Support Vector Machines
- 019 Regression and Classification Models
- 020 The Data set for the Regression problem
- 021 Importing data for regression model
- 022 Missing value treatment
- 023 Dummy Variable creation
- 024 X-y Split
- 025 Test-Train Split
- 026 Standardizing the data
- 027 SVM based Regression Model in Python
- 028 The Data set for the Classification problem
- 029 Classification model - Preprocessing
- 030 Classification model - Standardizing the data
- 031 SVM Based classification model
- 032 Hyper Parameter Tuning
- 033 Polynomial Kernel with Hyperparameter Tuning
- 034 Radial Kernel with Hyperparameter Tuning
A technology-based analytics education company
Founded by Abhishek Bansal and Pukhraj Parikh, Start-Tech Academy is a technology-based analytics education company and aims at bringing together the analytics companies and interested Learners.
Our top quality training content along with internships and project opportunities helps students in launching their Analytics journey.
Working as a Project manager in an Analytics consulting firm, Pukhraj has multiple years of experience working on analytics tools and software. He is competent in MS office suites, Cloud computing, SQL, Tableau, SAS, Google analytics and Python.
Abhishek worked as an Acquisition Process owner in a leading telecom company before moving on to learning and teaching technologies like Machine Learning and Artificial Intelligence.
Start-Tech Academy Forever All Course Bundle
Unlock this bundle today to start enjoying every Start-Tech Academy course for life including every course uploaded so far and all future courses!