If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.
Этот курс входит в специализацию ''Специализация TensorFlow in Practice'
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
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Чему вы научитесь
Learn best practices for using TensorFlow, a popular open-source machine learning framework
Build a basic neural network in TensorFlow
Train a neural network for a computer vision application
Understand how to use convolutions to improve your neural network
Приобретаемые навыки
Computer VisionTensorflowMachine Learning
Карьерные результаты учащихся
40%
начал новую карьеру, пройдя эти курсы
43%
получил значимые преимущества в карьере благодаря этому курсу
12%
стал больше зарабатывать или получил повышение
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Курс 1 из 4 в программе
Гибкие сроки
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Промежуточный уровень
Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.
Прибл. 10 часа на выполнение
Предполагаемая нагрузка: 4 weeks, 4-5 hours/week
Английский
Субтитры: Английский, Испанский, Русский, Японский
Программа курса: что вы изучите
6 ч. на завершение
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.
6 ч. на завершение
4 видео ((всего 16 мин.)), 5 материалов для самостоятельного изучения, 3 тестов
4 видео
A primer in machine learning3мин
The ‘Hello World’ of neural networks5мин
Working through ‘Hello World’ in TensorFlow and Python3мин
5 материала для самостоятельного изучения
Before you begin: TensorFlow 2.0 and this course10мин
From rules to data10мин
Try it for yourself10мин
Introduction to Google Colaboratory10мин
Week 1 Resources10мин
1 практическое упражнение
Week 1 Quiz
7 ч. на завершение
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!
7 ч. на завершение
7 видео ((всего 15 мин.)), 6 материалов для самостоятельного изучения, 3 тестов
7 видео
An Introduction to computer vision2мин
Writing code to load training data2мин
Coding a Computer Vision Neural Network2мин
Walk through a Notebook for computer vision3мин
Using Callbacks to control training1мин
Walk through a notebook with Callbacks1мин
6 материала для самостоятельного изучения
Exploring how to use data10мин
The structure of Fashion MNIST data10мин
See how it's done10мин
Get hands-on with computer vision1ч
See how to implement Callbacks10мин
Week 2 Resources10мин
1 практическое упражнение
Week 2 Quiz
8 ч. на завершение
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.
8 ч. на завершение
6 видео ((всего 19 мин.)), 6 материалов для самостоятельного изучения, 3 тестов
6 видео
What are convolutions and pooling?2мин
Implementing convolutional layers1мин
Implementing pooling layers4мин
Improving the Fashion classifier with convolutions4мин
Walking through convolutions3мин
6 материала для самостоятельного изучения
Coding convolutions and pooling layers10мин
Learn more about convolutions10мин
Getting hands-on, your first ConvNet10мин
Try it for yourself1ч
Experiment with filters and pools1ч
Week 3 Resources10мин
1 практическое упражнение
Week 3 Quiz
9 ч. на завершение
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 ч. на завершение
9 видео ((всего 27 мин.)), 10 материалов для самостоятельного изучения, 3 тестов
9 видео
Understanding ImageGenerator4мин
Defining a ConvNet to use complex images2мин
Training the ConvNet with fit_generator2мин
Walking through developing a ConvNet2мин
Walking through training the ConvNet with fit_generator3мин
Adding automatic validation to test accuracy4мин
Exploring the impact of compressing images3мин
A conversation with Andrew1мин
10 материала для самостоятельного изучения
Explore an impactful, real-world solution10мин
Designing the neural network10мин
Train the ConvNet with ImageGenerator10мин
Exploring the solution10мин
Training the neural network10мин
Experiment with the horse or human classifier1ч
Get hands-on and use validation30мин
Get Hands-on with compacted images30мин
Week 4 Resources10мин
Wrap up10мин
1 практическое упражнение
Week 4 Quiz
Рецензии
Лучшие отзывы о курсе INTRODUCTION TO TENSORFLOW FOR ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, AND DEEP LEARNING
от партнера JJApr 27, 2019
Very well organized. Good speakers. Content is comprehensive for a Introductory Course. A little more explanation on Validation versus Testing and on some of the evaluation functions would be helpful.
от партнера ASMar 8, 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?
от партнера RDAug 13, 2019
Great course to get started with building Convolutional Neural Networks in Keras for building Image Classifiers. This is probably the best way to get beginners into Deep Learning for Computer Vision.
от партнера MGMar 26, 2020
this course was helpful for me to learn more about CNN. it starts from basic concepts and improve that slowly and step by step. i truthfully recommend how what to start working with neural networks.
от партнера RAJan 13, 2020
Learn alot from this course, specially the steps required from importing data to train data from simple to real world examples. Further explanation of each line of code also demonstrate thoroughly.
от партнера KPJun 22, 2019
An excellent introduction to Neural Networks! At times, the exercises were quite easy. If the instructor could give more external links to datasets, it would allow students to try it themselves.
от партнера TWAug 12, 2019
There is quite some bugs in the example exercise code. Hope they can improve this in the future. Despite that, the content of the course is well designed and is a good start for beginners in TF
от партнера MSFeb 29, 2020
The course should included some information of how the hyper parameters of different models should be tuned and what are their effects.\n\nApart of that, the course was very comprehensive !! :)
от партнера SRJul 28, 2019
It was great course to start hands-on in TensorFlow and convolution neural networks. I especially liked how the convolution feature viewing tool was used to see what the networks are learning.
от партнера DLOct 4, 2019
Simply Amazing Laurence! Please keep me posted on more content!!!! this is the best person to learn from he just has a way that clicks for me I hope anyone else that is taking this course!!!!
от партнера KSOct 9, 2019
It is my first course on Machine Learning and Deep Learning, it was amazing and they taught us with more hands on programs. This course is highly recommended for Machine Learning enthusiast.
от партнера AWJun 6, 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.
от партнера PNJan 13, 2020
This is a great course for starting with TensorFlow for real projects. This course provides many practical challenges which are really helpful for clearing the concepts of deep learning.
от партнера VCDec 21, 2019
Excellent! I'm looking forward to finishing this specialization. I just completed course 1 in just 2 days. It's interesting, and the tutor makes it easy by explaining everything clearly.
от партнера CRNov 23, 2019
It was good enough in an abstract level. For a serious ML practitioner wannabe, I highly recommend to take Andrew's Deep Learning course first, then move on to Tensorflow specialization.
от партнера HWMay 19, 2019
The course demystified simple computer vision classification use-cases by leveraging TensorFlow. This is a great follow-on course to Andrew Ng's 11-week Stanford Machine Learning course.
от партнера KSJul 4, 2019
More or less the course takes on Tensorflow's implementation of Keras rather than Tensorflow native env. It also only focuses on computer vision domain. Kind of misleading course title.
от партнера NKFeb 21, 2020
Great intro to TensorFlow and Deep Learning for the typical software engineer. Week 4 could have been a bit more detailed - Week 4 tries to cover too many stuff. Week 5 recommended :)
от партнера TNOct 17, 2019
This course gives a good introduction to tensorflow with explanations of each parameters used be it layers or filters. It mainly gives an experience of hands-on course on tensorflow.
от партнера PMMay 29, 2019
Really nice introduction to TensorFlow with Keras. Laurence Moroney is so didactic that makes complex problems to look easy. Really recommend as a first interaction with TensorFlow.
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deeplearning.ai
deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders.
Специализация TensorFlow in Practice: общие сведения
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.
Looking for more advanced TensorFlow content? Check out the new TensorFlow: Data and Deployment Specialization.
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