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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IBM이 강좌에 대하여
최근 조회 30,507회
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중급 단계
완료하는 데 약 8시간 필요
영어
자막: 프랑스어, 포르투갈어 (유럽), 러시아어, 영어, 스페인어
귀하가 습득할 기술
- Deep Learning
- Artificial Neural Network
- Artificial Intelligence (AI)
- Machine Learning
- keras
유연한 마감일
일정에 따라 마감일을 재설정합니다.
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
중급 단계
완료하는 데 약 8시간 필요
영어
자막: 프랑스어, 포르투갈어 (유럽), 러시아어, 영어, 스페인어
제공자:
IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
강의 계획표 - 이 강좌에서 배울 내용
완료하는 데 2시간 필요
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.
완료하는 데 2시간 필요
4개 동영상 (총 17분), 1 개의 읽기 자료, 2 개의 테스트
완료하는 데 1시간 필요
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.
완료하는 데 1시간 필요
4개 동영상 (총 22분)
완료하는 데 3시간 필요
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.
완료하는 데 3시간 필요
3개 동영상 (총 16분)
완료하는 데 2시간 필요
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.
완료하는 데 2시간 필요
4개 동영상 (총 17분)
검토
INTRODUCTION TO DEEP LEARNING & NEURAL NETWORKS WITH KERAS의 최상위 리뷰
AB 제공2020년 3월 15일
Interesting course. Forward propagation, gradient descent, backward propagation, the vanishing gradient problem, (+ Regression, Classification, and CNN with Keras) explained clearly.
AM 제공2020년 6월 24일
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.
MC 제공2020년 2월 19일
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.
AS 제공2020년 3월 19일
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.
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