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.

Сессии:
  • 1 октября 2012, 8 недель
Характеристики онлайн курса:
  • Бесплатный:
  • Платный:
  • Сертификат:
  • MOOC:
  • Видеолекции:
  • Аудиолекции:
  • Email-курс:
  • Язык: Английский Gb

Отзывы

Пока никто не написал отзыв по этому курсу. Хотите быть первым?

Зарегистрируйтесь, чтобы оставить отзыв

Входит в подборки курсов:
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.
Ещё курсы на эту тему:
9-67s01 Object and Face Recognition
Provides a comprehensive introduction to key issues and findings in object recognition...
Small-icon.hover Scientific Computing
Investigate the flexibility and power of project-oriented computational analysis...
Xylscejy8t3gmrnlodrerh8kpnqaxng8ofy9aj8hjhm44-hvyisis32yy2rqknta3syn4yxuegk7nnjtpg=s0#w=436&h=268 Intro to Algorithms. Social Network Analysis
This class will give you an introduction to the design and analysis of algorithms...
6-854jf05 Advanced Algorithms (Fall 2005)
This course is a first-year graduate course in algorithms. Emphasis is placed...
9-641js05 Introduction to Neural Networks
This course explores the organization of synaptic connectivity as the basis...
Ещё из рубрики «Математика и статистика»:
Implementing_etl_with_ssis_378x225_0 Implementing ETL with SQL Server Integration Services (SSIS)
Learn how to use SSIS to build high performance integration solutions and ETL...
Data_quality_services_378x225 Data Cleansing with Data Quality Services (DQS)
A straightforward, no-nonsense approach to improving your data cleansing skills...
Dat226x_mds_378x225 Creating a Master Data Solution with SQL Server Master Data Services (MDS)
Learn how to manage Master Data Management (MDM) solutions with SQL Server 2016...
Course_image_378x225 How to Win Coding Competitions: Secrets of Champions
Enhance programming skills to boost your career and win prizes led by ITMO University...
01139732x-course_card_image-378x225_0 Mathematical Modeling in the Life Sciences 生物数学建模
学习使用数学建模的方法并通过定量和定性分析模型更好地理解生物现象。Learn to use mathematical models to gain a...
Ещё от 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...

© 2013-2017