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[#Udemy Free] #MachineLearning: A Beginners' Friendly Introduction


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Don't enroll if you're not going to watch all the lectures  (it's only 30 min)

What am I going to get from this course?
  • A clear understanding of the main algorithms used in machine learning
  • The Linear Regression method.
  • The Naive Bayes Algorithm.
  • The Decision Tree.
  • The Logistic Regression method.
  • The Neural Networks.
  • Support Vector Machines.
  • The Kernel Trick.

A friendly introduction to the main algorithms of Machine Learning with examples. No previous knowledge required.
Interested in the field of Machine Learning? Then this course is for you!
In this course, you'll learn the main algorithms used in machine learning quickly and easily with sample examples.
Machine Learning Essential Training is designed for EXTREME BEGINNERS who want to make their first step in machine learning and they've got no idea about it.
If that's the case with you, please hit the "Enroll" button. If you've already started with machine learning or you've learned the basics of machine learning or looking to dive deeper in the field, this course is not the right choice for you.
Machine Learning Essential Training is designed in a manner that promotes understanding throughout simple examples.
We don't dive into a deeper level of details about Machine Learning or the algorithms used in it; which can make the learning process complicated from a beginner's point of view; instead, I used simple examples in quick videos to make machine learning algorithms more simple to understand and easy to follow.
It've been quite hard for me to get a simple and easy to understand definition of machine learning, so I know that starting with complexe examples won't be informative. 
I've made this course as simple and short as possible to introduce anyone to machine learning.
We'll start by defining machine learning which is  a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can change when exposed to new data.
We'll then discover Logistic regression which is another technique borrowed by machine learning from the field of statistics. 
I'm glad that You've reached this point. You did really great. Now, there is only one smart decision to be made from your side: hit the "Enroll" button and you'll start a wonderfull machine learning journey 

What are the requirements?
  • Motivation and desire to learn.
  • Basic mathematic skills will help, but not required.
  • There are no other requirements to take this course.
What is the target audience?
  • Extreme beginners in machine learning.
  • Students who'd like to start with machine learning and want to understand the main algorithms of machine learning quickly and easily.
  • This course is not for you if you know the basics of machine learning.

This is the course description as seen on Udemy .
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