À propos de ce cours
4.8
20,000 ratings
•
2,293 reviews
You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience. After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error - Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance - Know how to apply end-to-end learning, transfer learning, and multi-task learning I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time. This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization....
Stacks

Cours 3 sur 5 dans la

Spécialisation Deep Learning
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.
Beginner Level

Niveau débutant

Clock

Recommandé : 2 weeks of study, 3-4 hours/week

Approx. 6 heures pour terminer
Comment Dots

English

Sous-titres : English, Chinese (Traditional), Chinese (Simplified), Korean, Turkish

Compétences que vous acquerrez

Machine LearningDeep LearningInductive TransferMulti-Task Learning
Stacks

Cours 3 sur 5 dans la

Spécialisation Deep Learning
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.
Beginner Level

Niveau débutant

Clock

Recommandé : 2 weeks of study, 3-4 hours/week

Approx. 6 heures pour terminer
Comment Dots

English

Sous-titres : English, Chinese (Traditional), Chinese (Simplified), Korean, Turkish

Programme du cours : ce que vous apprendrez dans ce cours

1

Section
Clock
2 heures pour terminer

ML Strategy (1)

...
Reading
13 vidéos (Total 100 min), 1 lecture, 1 quiz
Video13 vidéos
Why ML Strategy2 min
Orthogonalization10 min
Single number evaluation metric7 min
Satisficing and Optimizing metric5 min
Train/dev/test distributions6 min
Size of the dev and test sets5 min
When to change dev/test sets and metrics11 min
Why human-level performance?5 min
Avoidable bias6 min
Understanding human-level performance11 min
Surpassing human-level performance6 min
Improving your model performance4 min
Andrej Karpathy interview15 min
Reading1 lectures
Machine Learning flight simulator2 min
Quiz1 exercices pour s'entraîner
Bird recognition in the city of Peacetopia (case study)45 min

2

Section
Clock
3 heures pour terminer

ML Strategy (2)

...
Reading
11 vidéos (Total 132 min), 1 quiz
Video11 vidéos
Carrying out error analysis10 min
Cleaning up incorrectly labeled data13 min
Build your first system quickly, then iterate6 min
Training and testing on different distributions10 min
Bias and Variance with mismatched data distributions18 min
Addressing data mismatch10 min
Transfer learning11 min
Multi-task learning12 min
What is end-to-end deep learning?11 min
Whether to use end-to-end deep learning10 min
Ruslan Salakhutdinov interview17 min
Quiz1 exercices pour s'entraîner
Autonomous driving (case study)45 min
4.8
Direction Signs

35%

a commencé une nouvelle carrière après avoir terminé ces cours
Briefcase

83%

a bénéficié d'un avantage concret dans sa carrière grâce à ce cours
Money

14%

a obtenu une augmentation de salaire ou une promotion

Meilleurs avis

par AM•Nov 23rd 2017

I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.

par ZZ•Apr 7th 2018

A lot of concrete examples, including those in the lectures and in the tests. Gained some thoughts on how to manage a ML project. Thanks Andrew and deeplearning.ai for providing such a great course.

Enseignants

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.ai

À propos de deeplearning.ai

deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders....

À propos de la Spécialisation 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....
Deep Learning

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 enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. 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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