About this SVM e-book
Is it possible to perform SVM in Excel with mere spreadsheet without macro programming ? The answer is YES. This tutorial will explain how to do it step by step.
If you have ever read any other books on SVM, you will know how notoriously difficult it is to understand SVM. It is not the case with this tutorial. This tutorial is for real beginners with more than 60 figures and illustrations. You can enjoy reading the sample of the first two sections of SVM tutorial here. You can see that the difficult topics have been transformed into systematic and very simple explanations. In this e-book, you will learn how to perform training on Support Vector Machines, evaluating SVM training and predicting with SVM by a complete numerical examples for linearly separable as well as for linearly non-separable cases. You will learn how to use slack variables, kernel trick and well as kernel transformation through examples in Microsoft Excel. The e-book also discussed about SVM for multi classes, the strengths and weaknesses of SVM, when to use and when not to use SVM. Step by step on solving dual problem of SVM is also discussed. What is more, the e-book also comes with many spreadsheet companion files that include your own practice worksheets and the complete solutions. The complete solution include SVM training, evaluation and prediction. This e-book SVM tutorial and its companion files are designed to greatly enhance your understanding of SVM in very gentle way but fast to learn. With this e-book as your guide, learning SVM becomes easy steps and enjoyable practice moment.
You cannot find this information of doing SVM only using Spreadsheet without programming anywhere else!
What is SVM?
Support Vector Machines (SVM) is a supervised learning algorithm that classifies both linear and nonlinear data based on maximizing margin between support points and a nonlinear mapping to transform the original training data into a higher dimension. SVM was originally developed by Vapnik and Cortes and colleagues in 1992 based on the groundwork from Vapnik & Chervonenkis statistical learning theory in 1960s. SVM has been successfully applied in many applications including handwritten recognition, time-series prediction, speech Recognition, database marketing, protein sequence problem, breast cancer diagnosis and many more.
This tutorial will give you a very gentle introduction to SVM by giving simple step by step numerical solution using Microsoft Excel (and Python in the Appendix). You will learn about how you can train the SVM model, how to evaluate and use the SVM model to predict the classification. You will also learn by complete numerical example about how to handle linearly non-separable cases using slack variables and kernel tricks. By reading and do the practice of the numerical examples of this tutorial to the end, at least you will be able to ready to read other more advanced SVM books.
The e-book also comes with spreadsheet companion files that include your own practice worksheets and the complete solutions. The complete solution include SVM training, evaluation and prediction. This e-book SVM tutorial and its companion files are designed to greatly enhance your understanding of SVM in very gentle and fast to learn. With this e-book as your first guide, learning SVM becomes easy steps and enjoyable practice moment.
Why do you need to download this e-book and its companion files NOW?
- Gain full understanding . Your memory about your new understanding about this fascinating topic is still fresh. If you download it now, you will easily understand the detail of the tutorial. If you do it next time, you might have forgotten the understanding that has gained today.
- Save your learning time . Your time is very valuable. It saves a lot of your time to do self study on this topic.
- Understanding this topic will enhance your study , your work, and your research. Eventually you can develop it further to get more money for your future.
- Tired of ads? By purchasing the FULL tutorial, you will be able to read tutorial in a very nice PDF format without advertising . You can zoom in and out to see the formulas clearly. You can read in any computing device (phone, tablet, PC, laptop, Mac, iPad).
- The full tutorial also comes in e-book together with the companion files . This option will give you an eye opener to this fascinating topic. It enhances your understanding. The complete tutorial will be your self-study guide to improve your learning process. You can read it off-line anywhere anytime even when you don't have internet connection.
Testimonials
A few comments from customers who bought this tutorial
Thank you. Easy and efficient tutorial. Good value for money < Luciano Foglietti > |
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I saw your facebook post regarding your new book on SVM tutorial and implementation in Excel. I'm amazed at the fact that complex things like dynamic programming and the other heavy math of SVM can be done in excel.<Raphael Alampay> |
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Your SVM tutorial is excellent and the most useful tutorial I have ever seen. Thank you very much for your effort < Dr. Mitat Uysal > |
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You have turn Excel into magic wand. You?d done a great job! <Alexander Hindarmin> |
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I have read 3 books in SVM and I still could not understand. After reading your tutorial, only in a few minutes suddenly everything make sense now. Thank you! <Adam T. Juarez> |
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It?s simply amazing! <Noboyuki Y.> |
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I should have bought this tutorial 6 months ago to avoid the difficulties that I had with SVM. You are great teacher Dr Teknomo! <Mohammed Yusuf> |
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You made it in Excel. I thought it would be impossible. <Stephan Scott> |
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This is the best SVM book I have read so far. <Raj Chandra> |
What you will get when you download it NOW?
In this more than 70 pages Support Vector Machines Tutorial e-book you will learn, you will learn the following fascinating topics in a very SHORT TIME:
- Supervised Learning Illustrative Example
- What is SVM? An intuitive introduction
- Linearly Separable Case
- SVM Training in Excel for Two Linearly Separable Cases
- Evaluating SVM Training
- Class Prediction with SVM
- Linearly Non Separable Case
- SVM using Slack Variables
- Numerical Example in Excel of SVM with Slack Variables
- The Kernel Trick
- Examples of Kernel Transformation in Excel
- Numerical Example for SVM training with Kernel and Slack Variables
- SVM for Multi classes
- Winner takes all
- Pair-wise classification
- What is the strength of SVM?
- What is the weakness or limitation of SVM?
- When to use SVM?
- Solving Dual Problem of SVM Formula
- SVM in Python
- How to Detect Overfitting using Support Vector
- Training Performance
- Training with Polynomial Kernel
- Training with RBF Kernel
See the comparison table below for the options.
Consider to treat us lunch to teach you this fascinating knowledge. The price of our tutorial is so cheap that it is probably even cheaper than the cost of your lunch.
How to purchase this tutorial?
- Click Buy Now button above. You will be redirected to PayPal web site for payment.
- Register your email in PayPal (if you have not done it yet). You can purchase without PayPal registration but it will take at least 24 hours to get your tutorial.
- After your payment, PayPal will give you automatic redirect link to the download page of the tutorial. You can get the e-book and the companion files immediately after the purchase.
Teachers who want to use this e-book or the companion files for students in a class can contact us to purchase the e-book license in bulk.
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