Deep Learning

Through our guided lectures and labs, you'll first learn Neural Networks, and an overview of Deep Learning, then get hands-on experience using TensorFlow library to apply deep learning on different data types to solve real world problems.

3 Courses

Deep Learning Badge

About this Learning Path

In this learning path, you will be able to learn the basic concepts of Deep Leaning and TensorFlow. Then, you will get hands-on experience in solving problems using Deep Learning. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Average Course Rating

4.7 out of 5

Language

English

Badge Earned

Deep Learning

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Deep Learning Courses

Course

Deep Learning Fundamentals
This free course presents a holistic approach to Deep Learning and answers fundamental questions about what Deep Learning is and why it matters.

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Beginner Course Machine Learning

Accelerating Deep Learning with GPUs
Training complex deep learning models with large datasets takes along time. In this course, you will learn how to use accelerated GPU hardware to overcome the scalability problem in deep learning.

(100) Continue
Beginner Course Machine Learning

Deep Learning with TensorFlow
Majority of data in the world are unlabeled and unstructured data, for instance images, sound, and text data. Shallow neural networks cannot easily capture relevant structure in these kind of data, but deep networks are capable of discovering hidden structures within these data. In this course, you will use TensorFlow library to apply deep learning on different data types to solve real world problems.

(155) Continue

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