À propos de ce cours
4.6
2,559 ratings
646 reviews
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. This course contains the same content presented on Coursera beginning in 2013. It is not a continuation or update of the original course. It has been adapted for the new platform. Please be advised that the course is suited for an intermediate level learner - comfortable with calculus and with experience programming (Python)....
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Cours en ligne à 100 %

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
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Dates limites flexibles

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Clock

Recommandé : 5 hours/week

Approx. 45 heures pour terminer
Comment Dots

English

Sous-titres : English

Compétences que vous acquerrez

Artificial Neural NetworkRestricted Boltzmann MachineDeep LearningRecurrent Neural Network
Globe

Cours en ligne à 100 %

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Calendar

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.
Clock

Recommandé : 5 hours/week

Approx. 45 heures pour terminer
Comment Dots

English

Sous-titres : English

Programme du cours : ce que vous apprendrez dans ce cours

1

Section
Clock
2 heures pour terminer

Introduction

Introduction to the course - machine learning and neural nets...
Reading
5 vidéos (Total 43 min), 8 lectures, 1 quiz
Video5 vidéos
What are neural networks? [8 min]8 min
Some simple models of neurons [8 min]8 min
A simple example of learning [6 min]5 min
Three types of learning [8 min]7 min
Reading8 lectures
Syllabus and Course Logistics10 min
Lecture Slides (and resources)10 min
Setting Up Your Programming Assignment Environment10 min
Installing Octave on Windows10 min
Installing Octave on Mac OS X (10.10 Yosemite and 10.9 Mavericks)10 min
Installing Octave on Mac OS X (10.8 Mountain Lion and Earlier)10 min
Installing Octave on GNU/Linux10 min
More Octave10 min
Quiz1 exercice pour s'entraîner
Lecture 1 Quiz12 min

2

Section
Clock
1 heure pour terminer

The Perceptron learning procedure

An overview of the main types of neural network architecture ...
Reading
5 vidéos (Total 42 min), 1 lecture, 1 quiz
Video5 vidéos
Perceptrons: The first generation of neural networks [8 min]8 min
A geometrical view of perceptrons [6 min]6 min
Why the learning works [5 min]5 min
What perceptrons can't do [15 min]14 min
Reading1 lecture
Lecture Slides (and resources)10 min
Quiz1 exercice pour s'entraîner
Lecture 2 Quiz16 min

3

Section
Clock
1 heure pour terminer

The backpropagation learning proccedure

Learning the weights of a linear neuron ...
Reading
5 vidéos (Total 43 min), 2 lectures, 2 quiz
Video5 vidéos
The error surface for a linear neuron [5 min]5 min
Learning the weights of a logistic output neuron [4 min]3 min
The backpropagation algorithm [12 min]11 min
Using the derivatives computed by backpropagation [10 min]9 min
Reading2 lectures
Lecture Slides (and resources)10 min
Forward Propagation in Neural Networks10 min
Quiz2 exercices pour s'entraîner
Lecture 3 Quiz12 min
Programming Assignment 1: The perceptron learning algorithm.12 min

4

Section
Clock
1 heure pour terminer

Learning feature vectors for words

Learning to predict the next word...
Reading
5 vidéos (Total 44 min), 1 lecture, 1 quiz
Video5 vidéos
A brief diversion into cognitive science [4 min]4 min
Another diversion: The softmax output function [7 min]7 min
Neuro-probabilistic language models [8 min]7 min
Ways to deal with the large number of possible outputs [15 min]12 min
Reading1 lecture
Lecture Slides (and resources)10 min
Quiz1 exercice pour s'entraîner
Lecture 4 Quiz14 min
4.6
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Briefcase

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Meilleurs avis

par NSAug 13th 2017

Although It was way too tough for me, but you have to agree that you learn a lot throughout the course.\n\nI'll definitely pursue some other courses related to Deep Learning here.\n\nThanks Coursera.

par NRDec 2nd 2017

I would like to thank you all for this great course. To Prof Hinton, especially, it's amazing how much value is in this course and to make it available for entire world is just great. Thanks again !

Enseignant

Geoffrey Hinton

Professor
Department of Computer Science

À propos de University of Toronto

Established in 1827, the University of Toronto has one of the strongest research and teaching faculties in North America, presenting top students at all levels with an intellectual environment unmatched in depth and breadth on any other Canadian campus. ...

Foire Aux Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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