How neural networks work - a glimpse into math for beginners
4.8 (8 ratings)
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How neural networks work - a glimpse into math for beginners

a practical crash course in the mathematical concept used in neural networks for beginners
4.8 (8 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
41 students enrolled
Created by Daniel We
Last updated 7/2017
English
Current price: $10 Original price: $30 Discount: 67% off
5 hours left at this price!
30-Day Money-Back Guarantee
Includes:
  • 1 hour on-demand video
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • You know how to implement Gradient Descent. We use a linear regression as an example but the idea is completely transferable to neural networks
View Curriculum
Requirements
  • Basic knowlege of python syntax is helpful
  • your personal interest in the topic
  • Knowledge of math e.g. calculus is benefitial
Description

What is machine learning / ai ? How to lean machine learning in practice?

machine learning / ai (artificial intelligence) is the hottest topic in this century - for good reasons. Some people conceive it the "steam engine" of our century and one thing is certain: It will drastically change the world.

Neural Networks (often referred to as deep learning)  are particular interesting. But there are several questions to answer.

One of those is the math part involved in the construction of these neural networks. This is exactly were we want to start here.

This course is designed to give beginners a practical introduction to the mathematical concept. In this course we will use linear regression as an example to understand the math. The idea is completely transferable to neural networks. The change in coefficient works exactly the same.

If you are a complete beginner and want to get the main idea of  neural networks first then I suggest to start with my other course

"A crash course in neural networks for beginners" 

first.

Do you want to take your chance get a glimpse into the mathematical concept and expose yourself to this interesting topic which will change the world forever? Then join me and other students to dive deeper into neural networks right now. What are you waiting for?

See you in the first lecture



Who is the target audience?
  • beginners in neural networks who want to dig a little bit into math
  • beginners who want to learn the mathematical background applied in neural networks
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Curriculum For This Course
8 Lectures
01:08:29
+
Introduction - What are we covering here
8 Lectures 01:08:29



4 The error in our model
17:33

5 The concept of Gradient Descent
14:08

6 Finishing the implementation
10:38

7 Achieving the optimum
07:39

8 Final words
01:11
About the Instructor
Daniel We
4.6 Average rating
195 Reviews
4,967 Students
19 Courses
Traveller

Daniel is a 28 year old entrepreneur ,data scientist and web analyst consultant. He holds a master degree as well as other major certificates from Google and others.

He is committed to support other people by offering them educational services to help them accomplishing their goals and becomming the best in their profession.

"In order to do the impossible you need to see the invisible"