Informações sobre o curso
4.6
2,558 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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Sugerido: 5 hours/week

Aprox. 45 horas restantes
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English

Legendas: English

Habilidades que você terá

Artificial Neural NetworkRestricted Boltzmann MachineDeep LearningRecurrent Neural Network
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Clock

Sugerido: 5 hours/week

Aprox. 45 horas restantes
Comment Dots

English

Legendas: English

Programa - O que você aprenderá com este curso

1

Seção
Clock
2 horas para concluir

Introduction

Introduction to the course - machine learning and neural nets...
Reading
5 vídeos (Total de 43 min), 8 leituras, 1 teste
Video5 videos
What are neural networks? [8 min]8min
Some simple models of neurons [8 min]8min
A simple example of learning [6 min]5min
Three types of learning [8 min]7min
Reading8 leituras
Syllabus and Course Logistics10min
Lecture Slides (and resources)10min
Setting Up Your Programming Assignment Environment10min
Installing Octave on Windows10min
Installing Octave on Mac OS X (10.10 Yosemite and 10.9 Mavericks)10min
Installing Octave on Mac OS X (10.8 Mountain Lion and Earlier)10min
Installing Octave on GNU/Linux10min
More Octave10min
Quiz1 exercício prático
Lecture 1 Quiz12min

2

Seção
Clock
1 hora para concluir

The Perceptron learning procedure

An overview of the main types of neural network architecture ...
Reading
5 vídeos (Total de 42 min), 1 leitura, 1 teste
Video5 videos
Perceptrons: The first generation of neural networks [8 min]8min
A geometrical view of perceptrons [6 min]6min
Why the learning works [5 min]5min
What perceptrons can't do [15 min]14min
Reading1 leituras
Lecture Slides (and resources)10min
Quiz1 exercício prático
Lecture 2 Quiz16min

3

Seção
Clock
1 hora para concluir

The backpropagation learning proccedure

Learning the weights of a linear neuron ...
Reading
5 vídeos (Total de 43 min), 2 leituras, 2 testes
Video5 videos
The error surface for a linear neuron [5 min]5min
Learning the weights of a logistic output neuron [4 min]3min
The backpropagation algorithm [12 min]11min
Using the derivatives computed by backpropagation [10 min]9min
Reading2 leituras
Lecture Slides (and resources)10min
Forward Propagation in Neural Networks10min
Quiz2 exercícios práticos
Lecture 3 Quiz12min
Programming Assignment 1: The perceptron learning algorithm.12min

4

Seção
Clock
1 hora para concluir

Learning feature vectors for words

Learning to predict the next word...
Reading
5 vídeos (Total de 44 min), 1 leitura, 1 teste
Video5 videos
A brief diversion into cognitive science [4 min]4min
Another diversion: The softmax output function [7 min]7min
Neuro-probabilistic language models [8 min]7min
Ways to deal with the large number of possible outputs [15 min]12min
Reading1 leituras
Lecture Slides (and resources)10min
Quiz1 exercício prático
Lecture 4 Quiz14min
4.6
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Briefcase

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Melhores avaliações

por 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.

por 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 !

Instrutores

Geoffrey Hinton

Professor
Department of Computer Science

Sobre 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. ...

Perguntas Frequentes – FAQ

  • 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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