Building Deep Learning Models with TensorFlow
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.Learning Outcomes:
After completing this course, learners will be able to:
• explain foundational TensorFlow concepts such as the main functions, operations and the execution pipelines.
• describe how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions.
• understand different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.
• apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained.
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Syllabus
Syllabus - What you will learn from this course
Week 1
Introduction
Week 2
Supervised Learning Models
Week 3
Supervised Learning Models (Cont’d)
Week 4
Unsupervised Deep Learning Models
Week 5
Unsupervised Deep Learning Models (Cont’d) and scaling
FAQ
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Certificate?
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.
Reviews
i loved it. I have an undertsanding of different deep learning models
Good an simple videos to understand the concept. The notebooks are very detailed and give a second layer of knowledge with practical example
It is very good to explain concept of Deep Learning by Example , it is so clear, and better understand
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.
