AI Academy #2: Learn Classification & Clustering Methods A-Z | Udemy 100% Off Coupon

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AI Academy #2: Learn Classification & Clustering Methods A-Z.

Learn how to classify datasets using different methods like Bays, kNN, SVM and Logistic Regression (Codes Included).

What you’ll learn

  • Use k Nearest Neighbor classification method to classify datasets.
  • Classify datasets by using Support Vector Machine method
  • Learn main concept behind the k Nearest Neighbor classification method .
  • Understand main concept behind Support Vector Machine method.
  • Use different Kernel function for Support Vector Machine method
  • Use Naive Bayes classification method to classify datasets.
  • Classify Handwritten Images by Logistic classification method
  • Use Naive Bayes classification method to classify Pima Indian Diabetes Dataset.
  • Use Naive Bayes classification method to obtain probability of being male or female based on Height, Weight and FootSize.
  • Classify IRIS Flowers by Logistic classification method

Requirements

  • You should know about basic statistics
  • You must know basic python programming
  • Install Sublime and required library for python
  • You should have a great desire to learn programming and do it in a hands-on fashion, without having to watch countless lectures filled with slides and theory.
  • All you need is a decent PC/Laptop (2GHz CPU, 4GB RAM). You will get the rest from me.

Description

Do you like to learn how to classify images and flowers with high accuracy?

Do you like to know how to use classification methods like Bayes to predict human gender with a few lines of codes?

Do you know you can predict the possibility of Diabetes using Classification Methods?

If you say Yes so read more …

Artificial neural networks (ANNs) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains. Such systems “learn” to perform tasks by considering examples, generally without being programmed with any task-specific rules.

In this course you learn how to classify datasets by k-Nearest Neighbors Classification Method to find the correct class for data and reduce error. Then you go further  You will learn how to classify output of model by using Naive Bayes Classification Method.

In the first section you learn how to use python to estimate output of your system. In this section you can classify:

  • Python Dataset
  • IRIS Flowers
  • Make your own k Nearest Neighbors Algorithm

In the second section you learn how to use python to classify output of your system with nonlinear structure .In this section you can classify:

  • IRIS Flowers
  • Pima Indians Diabetes Database
  • Make your own Naive Bayes  Algorithm

You can also learn how to classify datasets by by Support Vector Machines to find the correct class for data and reduce error. Next you go further  You will learn how to classify output of model by using Logistic Regression

In the third section you learn how to use python to estimate output of your system. In this section you can estimate output of:

  • Random dataset
  • IRIS Flowers
  • Handwritten Digits

In the fourth section you learn how to use python to classify output of your system with nonlinear structure .In this section you can estimate output of:

  • Blobs
  • IRIS Flowers
  • Handwritten Digits

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Important information before you enroll:

  • In case you find the course useless for your career, don’t forget you are covered by a 30 day money back guarantee, full refund, no questions asked!
  • Once enrolled, you have unlimited, lifetime access to the course!
  • You will have instant and free access to any updates I’ll add to the course.
  • You will give you my full support regarding any issues or suggestions related to the course.
  • Check out the curriculum and FREE PREVIEW lectures for a quick insight.

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It’s time to take Action!

Click the “Take This Course” button at the top right now!

...Don’t waste time! Every second of every day is valuable

I can’t wait to see you in the course!

Best Regrads,

Sobhan

Who is the target audience?

  • Anyone who wants to make the right choice when starting to learn kNN & Bayes Classification method.
  • Anyone who wants to make the right choice when starting to learn SVM & Logistic Classifier methods.
  • Anyone who wants to make the right choice when starting to learn SVM & Logistic Classifier methods.
  • students who want to learn machine learning
  • Data analyser, Researcher, Engineers and Post Graduate Students need accurate and fast regression method.
  • Modelers, Statisticians, Analysts and Analytic Professional.
Category: Academics, Math & Science, Artificial Intelligence
Instructor: Sobhan N.
Language: English
Price: $149.99 Free (100 % off coupon code) ENROLL NOW