Este curso forma parte de Programa Especializado - Deep Learning
Neural Networks and Deep Learning
ofrecido por
Acerca de este Curso
4.9
38,471 calificaciones
If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" that will let you build AI systems that just weren't possible a few years ago.
In this course, you will learn the foundations of deep learning. When you finish this class, you will:
- Understand the major technology trends driving Deep Learning
- Be able to build, train and apply fully connected deep neural networks
- Know how to implement efficient (vectorized) neural networks
- Understand the key parameters in a neural network's architecture
This course also teaches you how Deep Learning actually works, rather than presenting only a cursory or surface-level description. So after completing it, you will be able to apply deep learning to a your own applications. If you are looking for a job in AI, after this course you will also be able to answer basic interview questions.
This is the first course of the Deep Learning Specialization.
Habilidades que obtendrás
Artificial Neural NetworkBackpropagationPython ProgrammingDeep Learning
Programa - Qué aprenderás en este curso
Week
1Introduction to deep learning
Be able to explain the major trends driving the rise of deep learning, and understand where and how it is applied today.
7 videos (Total: 76 min), 2 readings, 1 quiz
7 videos
Welcome5m
What is a neural network?7m
Supervised Learning with Neural Networks8m
Why is Deep Learning taking off?10m
About this Course2m
Course Resources1m
Geoffrey Hinton interview40m
2 lecturas
Frequently Asked Questions10m
How to use Discussion Forums10m
1 ejercicio de práctica
Introduction to deep learning20m
Week
2Neural Networks Basics
Learn to set up a machine learning problem with a neural network mindset. Learn to use vectorization to speed up your models.
19 videos (Total: 161 min), 2 readings, 3 quizzes
19 videos
Logistic Regression5m
Logistic Regression Cost Function8m
Gradient Descent11m
Derivatives7m
More Derivative Examples10m
Computation graph3m
Derivatives with a Computation Graph14m
Logistic Regression Gradient Descent6m
Gradient Descent on m Examples8m
Vectorization8m
More Vectorization Examples6m
Vectorizing Logistic Regression7m
Vectorizing Logistic Regression's Gradient Output9m
Broadcasting in Python11m
A note on python/numpy vectors6m
Quick tour of Jupyter/iPython Notebooks3m
Explanation of logistic regression cost function (optional)7m
Pieter Abbeel interview16m
2 lecturas
Deep Learning Honor Code2m
Programming Assignment FAQ10m
1 ejercicio de práctica
Neural Network Basics20m
Week
3Shallow neural networks
Learn to build a neural network with one hidden layer, using forward propagation and backpropagation.
12 videos (Total: 109 min), 2 quizzes
12 videos
Neural Network Representation5m
Computing a Neural Network's Output9m
Vectorizing across multiple examples9m
Explanation for Vectorized Implementation7m
Activation functions10m
Why do you need non-linear activation functions?5m
Derivatives of activation functions7m
Gradient descent for Neural Networks9m
Backpropagation intuition (optional)15m
Random Initialization7m
Ian Goodfellow interview14m
1 ejercicio de práctica
Shallow Neural Networks20m
Week
4Deep Neural Networks
Understand the key computations underlying deep learning, use them to build and train deep neural networks, and apply it to computer vision.
8 videos (Total: 64 min), 3 quizzes
8 videos
Forward Propagation in a Deep Network7m
Getting your matrix dimensions right11m
Why deep representations?10m
Building blocks of deep neural networks8m
Forward and Backward Propagation10m
Parameters vs Hyperparameters7m
What does this have to do with the brain?3m
1 ejercicio de práctica
Key concepts on Deep Neural Networks20m
38%
83%
10%
Principales revisiones
por JP•Feb 12th 2018
I would love some pointers to additional references for each video. Also, the instructor keeps saying that the math behind backprop is hard. What about an optional video with that? Otherwise, awesome!
por MZ•Sep 13th 2018
This course is really great.The lectures are really easy to understand and grasp.The assignment instructions are really helpful and one does not need to know python before hand to complete the course.
Instructores
Andrew Ng
Co-founder, Coursera; Adjunct Professor, Stanford University; formerly head of Baidu AI Group/Google Brain
Head Teaching Assistant - Kian Katanforoosh
Lecturer of Computer Science at Stanford University, deeplearning.ai, Ecole CentraleSupelec
Teaching Assistant - Younes Bensouda Mourri
Mathematical & Computational Sciences, Stanford University, deeplearning.aiAcerca de deeplearning.ai
deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders.
Acerca del programa especializado Deep Learning
If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning.
In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.
You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice.
AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work.
We will help you master Deep Learning, understand how to apply it, and build a career in AI.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
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