Looking to start a career in Deep Learning? Look no further. This course will introduce you to the field of deep learning and help you answer many questions that people are asking nowadays, like what is deep learning, and how do deep learning models compare to artificial neural networks? You will learn about the different deep learning models and build your first deep learning model using the Keras library.
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このコースについて
91,289 最近の表示
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における6の3コース
柔軟性のある期限
スケジュールに従って期限をリセットします。
中級レベル
約9時間で修了
英語
字幕：英語
習得するスキル
Deep LearningArtificial Neural NetworkArtificial Intelligence (AI)Machine Learningkeras
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における6の3コース
柔軟性のある期限
スケジュールに従って期限をリセットします。
中級レベル
約9時間で修了
英語
字幕：英語
提供：
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.
シラバス - 本コースの学習内容
2時間で修了
Introduction to Neural Networks and Deep Learning
In this module, you will learn about exciting applications of deep learning and why now is the perfect time to learn deep learning. You will also learn about neural networks and how most of the deep learning algorithms are inspired by the way our brain functions and the neurons process data. Finally, you will learn about how neural networks feed data forward through the network.
2時間で修了
4件のビデオ （合計17分）, 1 reading, 2 quizzes
4件のビデオ
Welcome2 分
Introduction to Deep Learning4 分
Neurons and Neural Networks3 分
Artificial Neural Networks5 分
1件の学習用教材
Syllabus10 分
1の練習問題
Introduction to Neural Networks and Deep Learning30 分
1時間で修了
Artificial Neural Networks
In this module, you will learn about the gradient descent algorithm and how variables are optimized with respect to a defined function. You will also learn about backpropagation and how neural networks learn and update their weights and biases. Futhermore, you will learn about the vanishing gradient problem. Finally, you will learn about activation functions.
1時間で修了
4件のビデオ （合計22分）
1の練習問題
Artificial Neural Networks30 分
3時間で修了
Keras and Deep Learning Libraries
In this module, you will learn about the diifferent deep learning libraries namely, Keras, PyTorch, and TensorFlow. You will also learn how to build regression and classification models using the Keras library.
3時間で修了
3件のビデオ （合計16分）
1の練習問題
Keras and Deep Learning Libraries30 分
2時間で修了
Deep Learning Models
In this module, you will learn about the difference between the shallow and deep neural networks. You will also learn about convolutional networks and how to build them using the Keras library. Finally, you will also learn about recurrent neural networks and autoencoders.
2時間で修了
4件のビデオ （合計17分）
4件のビデオ
Convolutional Neural Networks8 分
Recurrent Neural Networks2 分
Autoencoders2 分
1の練習問題
Deep Learning Models30 分
レビュー
INTRODUCTION TO DEEP LEARNING & NEURAL NETWORKS WITH KERAS からの人気レビュー
ABにより2020年3月15日
Interesting course. Forward propagation, gradient descent, backward propagation, the vanishing gradient problem, (+ Regression, Classification, and CNN with Keras) explained clearly.
AMにより2020年6月24日
Good course. It is a very direct approach. It is a basic introduction to keras. Doing the labs is recommended, and also previous knowledge about machine learning is encouraged.
ASにより2020年3月19日
A good course. Could be better if it was explained how to select the optimal number of layers and nodes. This was not covered and explained anywhere. Overall it was good.
MCにより2020年2月19日
Best suited for beginner in Deep learning with Keras. Good content, hands on experience with Jupiter notebook with IBM Developer tool. Worked Exercise code for CNN & RNN.
IBM AI Engineering プロフェッショナル認定について
The rapid pace of innovation in Artificial Intelligence (AI) is creating enormous opportunity for transforming entire industries and our very existence. After competing this comprehensive 6 course Professional Certificate, you will get a practical understanding of Machine Learning and Deep Learning.
You will master fundamental concepts of Machine Learning and Deep Learning, including supervised and unsupervised learning. You will utilize popular Machine Learning and Deep Learning libraries such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow applied to industry problems involving object recognition and Computer Vision, image and video processing, text analytics, Natural Language Processing, recommender systems, and other types of classifiers.
You will be able to scale Machine Learning on Big Data using Apache Spark. You will build, train, and deploy different types of Deep Architectures, including Convolutional Networks, Recurrent Networks, and Autoencoders.
By the end of this Professional Certificate, you will have completed several projects showcasing your proficiency in Machine Learning and Deep Learning, and become armed with skills for a career as an AI Engineer.
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When you enroll in the course, you get access to all of the courses in the Certificate, 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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If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
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