The majority of data in the world is unlabeled and unstructured. Shallow neural networks cannot easily capture relevant structure in, for instance, images, sound, and textual data. Deep networks are capable of discovering hidden structures within this type of data. In this course you’ll use TensorFlow library to apply deep learning to different data types in order to solve real world problems.
Этот курс входит в специализацию ''Профессиональная сертификация 'IBM AI Engineering''
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Об этом курсе
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Сертификат, ссылками на который можно делиться с другими людьми
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Курс 5 из 6 в программе
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Средний уровень
Прибл. 13 часов на выполнение
Английский
Субтитры: Английский
Преподаватели
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Курс 5 из 6 в программе
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Средний уровень
Прибл. 13 часов на выполнение
Английский
Субтитры: Английский
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IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
Программа курса: что вы изучите
5 ч. на завершение
Introduction
In this module, you will learn about TensorFlow, and use it to create Linear and Logistic Regression models.
5 ч. на завершение
5 видео ((всего 28 мин.)), 1 материал для самостоятельного изучения, 5 тестов
5 видео
Welcome2мин
Introduction to TensorFlow7мин
TensorFlow 2.x and Eager Execution4мин
Introduction to Deep Learning2мин
Deep Neural Networks11мин
1 материал для самостоятельного изучения
Syllabus10мин
1 практическое упражнение
Deep Neural Networks and TensorFlow30мин
2 ч. на завершение
Supervised Learning Models
In this module, you will learn about about Convolutional Neural Networks, and the building blocks of a convolutional neural network, such as convolution and feature learning. You will also learn about the popular MNIST database. Finally, you will learn how to build a Multi-layer perceptron and convolutional neural networks in Python and using TensorFlow.
2 ч. на завершение
3 видео ((всего 22 мин.))
3 видео
Convolutional Neural Networks (CNNs) for Classification4мин
Convolutional Neural Networks (CNNs) Architecture13мин
1 практическое упражнение
Convolutional Neural Networks30мин
3 ч. на завершение
Supervised Learning Models (Cont'd)
In this module, you will learn about the recurrent neural network model, and special type of a recurrent neural network, which is the Long Short-Term Memory model. Also, you will learn about the Recursive Neural Tensor Network theory, and finally, you will apply recurrent neural networks to language modelling.
3 ч. на завершение
4 видео ((всего 22 мин.))
4 видео
Recurrent Neural Networks (RNNs)5мин
The Long Short Term Memory (LSTM) Model5мин
Language Modelling7мин
1 практическое упражнение
Recurrent Neural Networks30мин
2 ч. на завершение
Unsupervised Deep Learning Models
In this module, you will learn about the applications of unsupervised learning. You will learn about Restricted Boltzmann Machines (RBMs), and how to train an RBM. Finally, you will apply Restricted Boltzmann Machines to build a recommendation system.
2 ч. на завершение
2 видео ((всего 10 мин.))
1 практическое упражнение
Restricted Boltzmann Machines30мин
Рецензии
Лучшие отзывы о курсе BUILDING DEEP LEARNING MODELS WITH TENSORFLOW
от партнера RR25 июля 2020 г.
Nice course to introduce you to more advanced neural network algorithms, I wish the evaluations were more challenging and based on practical exercises... there is no final assignment either.
от партнера HJ17 мая 2020 г.
It would have been nice if the video tutorials would explain the code section as well, and if there would have been some in-depth teaching of the code part. But this course did benefit.
от партнера RC14 мая 2020 г.
Good an simple videos to understand the concept. The notebooks are very detailed and give a second layer of knowledge with practical example
от партнера ZR2 июля 2020 г.
Deep Learning made me feel that there is a way to build models and classify data so easily and in a skillful way. Amazing course!
Профессиональная сертификация 'IBM AI Engineering': общие сведения
Artificial intelligence (AI) is revolutionizing entire industries, changing the way companies across sectors leverage data to make decisions. To stay competitive, organizations need qualified AI engineers who use cutting-edge methods like machine learning algorithms and deep learning neural networks to provide data driven actionable intelligence for their businesses. This 6-course Professional Certificate is designed to equip you with the tools you need to succeed in your career as an AI or ML engineer.
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