An Introduction to Practical Deep Learning
Overview
Class Central Tips
This course provides an introduction to Deep Learning, a field that aims to harness the enormous amounts of data that we are surrounded by with artificial neural networks, allowing for the development of self-driving cars, speech interfaces, genomic sequence analysis and algorithmic trading.
You will explore important concepts in Deep Learning, train deep networks using Intel Nervana Neon, apply Deep Learning to various applications and explore new and emerging Deep Learning topics.
You will explore important concepts in Deep Learning, train deep networks using Intel Nervana Neon, apply Deep Learning to various applications and explore new and emerging Deep Learning topics.
Syllabus
- Introduction to Deep Learning and Deep Learning Basics
- Convolutional Neural Networks (CNN), Fine-Tuning and Detection
- Recurrent Neural Networks (RNN)
- Training Tips and Multinode Distributed Training
- Hot Research and Intel's Roadmap
- Final Quiz
Taught by
Nikhil Murthy and Andres Rodriguez
Tags
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Reviews
3.0 rating, based on 1 reviews
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Sylvia Schmitt completed this course, spending 6 hours a week on it and found the course difficulty to be medium.
I completed this course after taking and completing the Machine Learning Course taught by Andrew Ng. Therefore, I must admit that I was a bit disappointed. Without the ML course taught by Andrew Ng, I would not had understood much of this course. But I did not learn a lot new things.
If you have already taken the before mentioned Machine Learning course, I would not recommend taking this one.
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