About this Course
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다음 전문 분야의 1개 강좌 중 1번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.

완료하는 데 약 8시간 필요

권장: 4 weeks, 4-5 hours/week...

영어

자막: 영어

배울 내용

  • Check

    Learn best practices for using TensorFlow, a popular open-source machine learning framework

  • Check

    Build a basic neural network in TensorFlow

  • Check

    Train a neural network for a computer vision application

  • Check

    Understand how to use convolutions to improve your neural network

귀하가 습득할 기술

Computer VisionTensorflowMachine Learning

다음 전문 분야의 1개 강좌 중 1번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.

완료하는 데 약 8시간 필요

권장: 4 weeks, 4-5 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 3시간 필요

A New Programming Paradigm

Welcome to this course on going from Basics to Mastery of TensorFlow. We're excited you're here! In week 1 you'll get a soft introduction to what Machine Learning and Deep Learning are, and how they offer you a new programming paradigm, giving you a new set of tools to open previously unexplored scenarios. All you need to know is some very basic programming skills, and you'll pick the rest up as you go along. To get started, check out the first video, a conversation between Andrew and Laurence that sets the theme for what you'll study...

...
4 videos (Total 16 min), 5 readings, 3 quizzes
4개의 동영상
A primer in machine learning3m
The ‘Hello World’ of neural networks5m
Working through ‘Hello World’ in TensorFlow and Python3m
5개의 읽기 자료
Learner Support10m
From rules to data10m
Try it for yourself10m
Introduction to Google Colaboratory10m
Week 1 Resources10m
1개 연습문제
Week 1 Quiz
2
완료하는 데 4시간 필요

Introduction to Computer Vision

Welcome to week 2 of the course! In week 1 you learned all about how Machine Learning and Deep Learning is a new programming paradigm. This week you’re going to take that to the next level by beginning to solve problems of computer vision with just a few lines of code! Check out this conversation between Laurence and Andrew where they discuss it and introduce you to Computer Vision!

...
7 videos (Total 15 min), 6 readings, 3 quizzes
7개의 동영상
An Introduction to computer vision2m
Writing code to load training data2m
Coding a Computer Vision Neural Network2m
Walk through a Notebook for computer vision3m
Using Callbacks to control training1m
Walk through a notebook with Callbacks1m
6개의 읽기 자료
Exploring how to use data10m
The structure of Fashion MNIST data10m
See how it's done10m
Get hands-on with computer vision1h
See how to implement Callbacks10m
Week 2 Resources10m
1개 연습문제
Week 2 Quiz
3
완료하는 데 5시간 필요

Enhancing Vision with Convolutional Neural Networks

Welcome to week 3! In week 2 you saw a basic Neural Network for Computer Vision. It did the job nicely, but it was a little naive in its approach. This week we’ll see how to make it better, as discussed by Laurence and Andrew here.

...
6 videos (Total 19 min), 6 readings, 3 quizzes
6개의 동영상
What are convolutions and pooling?2m
Implementing convolutional layers1m
Implementing pooling layers4m
Improving the Fashion classifier with convolutions4m
Walking through convolutions3m
6개의 읽기 자료
Coding convolutions and pooling layers10m
Learn more about convolutions10m
Getting hands-on, your first ConvNet10m
Try it for yourself1h
Experiment with filters and pools1h
Week 3 Resources10m
1개 연습문제
Week 3 Quiz
4
완료하는 데 6시간 필요

Using Real-world Images

Last week you saw how to improve the results from your deep neural network using convolutions. It was a good start, but the data you used was very basic. What happens when your images are larger, or if the features aren’t always in the same place? Andrew and Laurence discuss this to prepare you for what you’ll learn this week: handling complex images!

...
9 videos (Total 27 min), 10 readings, 3 quizzes
9개의 동영상
Understanding ImageGenerator4m
Defining a ConvNet to use complex images2m
Training the ConvNet with fit_generator2m
Walking through developing a ConvNet2m
Walking through training the ConvNet with fit_generator3m
Adding automatic validation to test accuracy4m
Exploring the impact of compressing images3m
Outro: A conversation with Andrew1m
10개의 읽기 자료
Explore an impactful, real-world solution10m
Designing the neural network10m
Train the ConvNet with ImageGenerator10m
Exploring the solution10m
Training the neural network10m
Experiment with the horse or human classifier1h
Get hands-on and use validation30m
Get Hands-on with compacted images30m
Week 4 Resources10m
Outro10m
1개 연습문제
Week 4 Quiz
4.7
403개의 리뷰Chevron Right

44%

이 강좌를 수료한 후 새로운 경력 시작하기

42%

이 강좌를 통해 확실한 경력상 이점 얻기

12%

급여 인상 또는 승진하기

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning의 최상위 리뷰

대학: ASMar 9th 2019

Good intro course, but google colab assignments need to be improved. And submitting a jupyter notebook was much more easier, why would I want to login to my google account to be a part of this course?

대학: AWJun 7th 2019

An awesome practical course that helps me to start creating my first neural networks using keras in such great methods, the instructor is very good at delivering the knowledge he has\n\n.

강사

Avatar

Laurence Moroney

AI Advocate
Google Brain

deeplearning.ai 정보

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

TensorFlow in Practice 전문 분야 정보

Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework. In this four-course Specialization, you’ll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network’s performance using convolutions as you train it to identify real-world images. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input data to a neural network. You’ll even train an AI to create original poetry! AI is already transforming industries across the world. After finishing this Specialization, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects. Courses 1-3 are available now, with Course 4 launching in July....
TensorFlow in Practice

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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