Building Deep Learning Models with TensorFlow
- 4.4
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Course Summary
Learn how to build deep learning models with TensorFlow, a powerful open-source software library for dataflow and differentiable programming across a range of tasks. This course will teach you everything you need to know to get started, from the basics of neural networks to advanced topics like convolutional neural networks and recurrent neural networks.Key Learning Points
- Learn how to use TensorFlow to build deep learning models
- Understand the basics of neural networks
- Explore advanced topics like convolutional and recurrent neural networks
Job Positions & Salaries of people who have taken this course might have
- USA: $112,000
- India: ₹1,000,000
- Spain: €36,000
- USA: $112,000
- India: ₹1,000,000
- Spain: €36,000
- USA: $96,000
- India: ₹800,000
- Spain: €30,000
- USA: $112,000
- India: ₹1,000,000
- Spain: €36,000
- USA: $96,000
- India: ₹800,000
- Spain: €30,000
- USA: $120,000
- India: ₹1,200,000
- Spain: €42,000
Related Topics for further study
Learning Outcomes
- Understand the basics of deep learning and neural networks
- Learn how to use TensorFlow to build and train deep learning models
- Explore advanced topics like convolutional and recurrent neural networks
Prerequisites or good to have knowledge before taking this course
- Basic programming knowledge (Python recommended)
- Familiarity with linear algebra and calculus
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Deep Learning Specialization
- Applied Data Science with Python Specialization
Related Education Paths
Related Books
Description
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.
Outline
- Introduction
- Welcome
- Introduction to TensorFlow
- TensorFlow 2.x and Eager Execution
- Introduction to Deep Learning
- Deep Neural Networks
- Syllabus
- Deep Neural Networks and TensorFlow
- Supervised Learning Models
- Introduction to Convolutional Neural Networks (CNNs)
- Convolutional Neural Networks (CNNs) for Classification
- Convolutional Neural Networks (CNNs) Architecture
- Convolutional Neural Networks
- Supervised Learning Models (Cont'd)
- The Sequential Problem
- Recurrent Neural Networks (RNNs)
- The Long Short Term Memory (LSTM) Model
- Language Modelling
- Recurrent Neural Networks
- Unsupervised Deep Learning Models
- Introduction to Restricted Boltzmann Machines
- Restricted Boltzmann Machines (RBMs)
- Restricted Boltzmann Machines
- Unsupervised Deep Learning Models (Cont'd) and scaling
- Introduction to Autoencoders
- Autoencoders
- Scaling of neural networks
Summary of User Reviews
Discover how to build deep learning models with TensorFlow on Coursera. Students praise the course's depth of knowledge and real-world applications, as well as its engaging and interactive format.Key Aspect Users Liked About This Course
Real-world applicationsPros from User Reviews
- In-depth knowledge and coverage of the subject matter
- Engaging and interactive format
- Real-world applications provide practical experience
- Great for those looking to deepen their understanding of deep learning
- Excellent course for beginners and experienced learners alike
Cons from User Reviews
- Some users found the course too focused on theory and lacking in practical exercises
- The assignments can be challenging and time-consuming
- Some users felt that the course was too fast-paced and difficult to follow
- Some users experienced technical difficulties with the platform
- The course may be too basic for advanced learners
Samaya Madhavan
4.4 Raiting
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- 0.0
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