Neural Networks for Machine Learning

Geoffrey Hinton, University of Toronto

Learn about artificial neural networks and how they're being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc. We'll emphasize both the basic algorithms and the practical tricks needed to get them to work well.

Neural networks use learning algorithms that are inspired by our understanding of how the brain learns, but they are evaluated by how well they work for practical applications such as speech recognition, object recognition, image retrieval and the ability to recommend products that a user will like. As computers become more powerful, Neural Networks are gradually taking over from simpler Machine Learning methods. They are already at the heart of a new generation of speech recognition devices and they are beginning to outperform earlier systems for recognizing objects in images. The course will explain the new learning procedures that are responsible for these advances, including effective new proceduresr for learning multiple layers of non-linear features, and give you the skills and understanding required to apply these procedures in many other domains.

This YouTube video gives examples of the kind of material that will be in the course, but the course will present this material at a much gentler rate and with more examples.

Recommended Background

Programming proficiency in Matlab, Octave or Python. Enough knowledge of calculus to be able to differentiate simple functions. Enough knowledge of linear algebra to understand simple equations involving vectors and matrices. Enough knowledge of probability theory to understand what a probability density is.

Course Format

The class will consist of lecture videos, which are between 5 and 15 minutes in length. These contain 1-3 integrated quiz questions per video. There will also be standalone homework that is not part of video lectures, optional programming assignments, and a (not optional) final test.

FAQ

  • Will I get a certificate after completing this class?

    Yes. Students who successfully complete the class will receive a certificate signed by the instructor.

  • What resources will I need for this class?

    You will need access to a computer that you can use to experiment with learning algorithms written in Matlab, Octave or Python. If you use Matlab you will need your own licence.

  • What is the coolest thing I'll learn if I take this class?

    You will learn how a neural network can generate a plausible completion of almost any sentence.

Dates:
  • 1 October 2012, 8 weeks
Course properties:
  • Free:
  • Paid:
  • Certificate:
  • MOOC:
  • Video:
  • Audio:
  • Email-course:
  • Language: English Gb

Reviews

No reviews yet. Want to be the first?

Register to leave a review

Show?id=n3eliycplgk&bids=695438
Included in selections:
Small-icon.hover Machine Learning
Machine learning: from the basics to advanced topics. Includes statistics...
Small-icon.hover Deep Learning
Good materials on deep learning.
NVIDIA
More on this topic:
Hst-722jf05 Brain Mechanisms for Hearing and Speech
An advanced course covering anatomical, physiological, behavioral, and computational...
9-012s02 The Brain and Cognitive Sciences II (Spring 2002)
This course is the second half of the intensive survey of brain and behavioral...
Small-icon.hover Computer Vision: From 3D Reconstruction to Visual Recognition
This course delivers a systematic overview of computer vision, emphasizing two...
22240_b028_9 Python for Beginners 2017 - Udemy
Learn Python Programming on the Mac or PC with "Python for Beginners" Python...
6-854jf05 Advanced Algorithms (Fall 2005)
This course is a first-year graduate course in algorithms. Emphasis is placed...
More from 'Mathematics, Statistics and Data Analysis':
5c7385bf-01ae-4f77-a628-1586471a91ac-3fc9f3407eac.small Evaluation of Predictive Modelling
Gain an in-depth understanding of evaluation and sampling approaches for...
Ef5dcb87-b65b-46a6-bb2a-c5a3f7807845-7cb915944555.small Engineering Calculus and Differential Equations
Learn fundamental concepts of single-variable calculus and ordinary differential...
07bd7954-0593-43cb-b0c4-0f18f5c25ee1-a5d93e120a6d.small Microsoft Professional Capstone : Data Science
Solve a real-world data science problem in this capstone project for the Microsoft...
7c25b549-84c0-4253-9cc8-6c9485666762-379f86464212.small Statistics for Business - II
Examine data drawn from allied fields of business such as Finance and HR, and...
1ddf76b7-93e0-4c7f-9ff6-75e99897159d-41611629f8f9.small Multi-Object Tracking for Automotive Systems
Learn how to localize and track dynamic objects with a range of applications...
More from 'Coursera':
Success-from-the-start-2 First Year Teaching (Secondary Grades) - Success from the Start
Success with your students starts on Day 1. Learn from NTC's 25 years developing...
New-york-city-78181 Understanding 9/11: Why Did al Qai’da Attack America?
This course will explore the forces that led to the 9/11 attacks and the policies...
Small-icon.hover Aboriginal Worldviews and Education
This course will explore indigenous ways of knowing and how this knowledge can...
Ac-logo Analytic Combinatorics
Analytic Combinatorics teaches a calculus that enables precise quantitative...
Talk_bubble_fin2 Accountable Talk®: Conversation that Works
Designed for teachers and learners in every setting - in school and out, in...

© 2013-2019