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2020-12-12 04:03:24
30-Day Money-Back Guarantee

This course includes:

  • 6 hours on-demand video
  • 2 articles
  • 3 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
Development Data Science Machine Learning

Support Vector Machines in Python: SVM Concepts & Code

Learn Support Vector Machines in Python. Covers basic SVM models to Kernel-based advanced SVM models of Machine Learning
Rating: 4.4 out of 54.4 (334 ratings)
67,169 students
Created by Start-Tech Academy
Last updated 11/2020
English
English [Auto]
30-Day Money-Back Guarantee

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

Course content

8 sections • 54 lectures • 6h 7m total length

  • Preview03:04
  • Course Resources
    00:05
  • Opening Jupyter Notebook
    09:06
  • Introduction to Jupyter
    13:26
  • Arithmetic operators in Python: Python Basics
    04:28
  • Strings in Python: Python Basics
    19:07
  • Lists, Tuples and Directories: Python Basics
    18:41
  • Working with Numpy Library of Python
    11:54
  • Working with Pandas Library of Python
    09:15
  • Working with Seaborn Library of Python
    08:57

  • Introduction to Machine Learning
    16:03
  • Building a Machine Learning Model
    08:42

  • Course flow
    01:34
  • The Concept of a Hyperplane
    04:55
  • Maximum Margin Classifier
    03:18
  • Preview02:28

  • Preview10:00
  • Limitations of Support Vector Classifiers
    01:34
  • Quiz
    1 question

  • Kernel Based Support Vector Machines
    06:45
  • Quiz
    2 questions

  • Regression and Classification Models
    00:46
  • The Data set for the Regression problem
    02:59
  • Importing data for regression model
    05:40
  • Missing value treatment
    03:38
  • Dummy Variable creation
    04:58
  • X-y Split
    04:02
  • Test-Train Split
    06:04
  • Standardizing the data
    06:28
  • SVM based Regression Model in Python
    10:08
  • The Data set for the Classification problem
    01:38
  • Classification model - Preprocessing
    08:24
  • Classification model - Standardizing the data
    01:57
  • SVM Based classification model
    11:28
  • Hyper Parameter Tuning
    09:47
  • Polynomial Kernel with Hyperparameter Tuning
    04:07
  • Radial Kernel with Hyperparameter Tuning
    06:31

  • Bonus Lecture
    00:25

  • Gathering Business Knowledge
    03:26
  • Data Exploration
    03:19
  • The Dataset and the Data Dictionary
    07:31
  • Importing Data in Python
    06:04
  • Univariate analysis and EDD
    03:34
  • EDD in Python
    12:11
  • Outlier Treatment
    04:15
  • Outlier Treatment in Python
    14:18
  • Missing Value Imputation
    03:36
  • Missing Value Imputation in Python
    04:57
  • Seasonality in Data
    03:35
  • Bi-variate analysis and Variable transformation
    16:14
  • Variable transformation and deletion in Python
    09:21
  • Non-usable variables
    04:44
  • Dummy variable creation: Handling qualitative data
    04:50
  • Dummy variable creation in Python
    05:45
  • Correlation Analysis
    10:05
  • Correlation Analysis in Python
    07:07
  • Quiz
    1 question

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?

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

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:

  • People pursuing a career in data science
  • Working Professionals beginning their Data journey
  • Statisticians needing more practical experience
  • Anyone curious to master SVM technique from Beginner to Advanced in short span of time

Instructor

Start-Tech Academy
1,700,000+ Enrollments | 4+ Rated | 160+ Countries
Start-Tech Academy
  • 4.3 Instructor Rating
  • 33,089 Reviews
  • 873,921 Students
  • 38 Courses

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. 

Founded by Abhishek Bansal and Pukhraj Parikh.

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.


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