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. After completing this course, learners will be able to: • describe what a neural network is, what a deep learning model is, and the difference between them. • demonstrate an understanding of unsupervised deep learning models such as autoencoders and restricted Boltzmann machines. • demonstrate an understanding of supervised deep learning models such as convolutional neural networks and recurrent networks. • build deep learning models and networks using the Keras library.
이 강좌는 IBM AI Engineering 전문 자격증의 일부입니다.
Introduction to Deep Learning & Neural Networks with Keras
제공자:
귀하가 습득할 기술
강의 계획 - 이 강좌에서 배울 내용
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.
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.
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.
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.
Introduction to Deep Learning & Neural Networks with Keras의 최상위 리뷰
The teaching is not deep enough to solve the Week 5 assignment, please take note you need to plumb in other Keras courses.
Very intractive and benificial course for me .Thank you coursera and IBM for this course
강사
Alex Aklson
Ph.D., Data ScientistIBM 정보
IBM AI Engineering 전문 자격증 정보
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
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.
이 수료 과정을 구독하면 무엇을 이용할 수 있나요?
강좌를 등록하면 수료 과정의 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.
환불 규정은 어떻게 되나요?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.
