Listen free for 30 days
-
Neural Networks and Deep Learning
- Neural Networks and Deep Learning, Deep Learning Explained to Your Granny (Machine Learning)
- Narrated by: Jason R. L. Brown
- Length: 3 hrs and 25 mins
Failed to add items
Sorry, we are unable to add the item because your shopping cart is already at capacity.
Add to Cart failed.
Please try again later
Add to Wish List failed.
Please try again later
Remove from wish list failed.
Please try again later
Follow podcast failed
Unfollow podcast failed
Pick 1 audiobook a month from our unmatched collection.
Listen all you want to thousands of included audiobooks, Originals, and podcasts.
Access exclusive sales and deals.
Premium Plus auto-renews for $14.95/mo + applicable taxes after 30 days. Cancel anytime.
Buy Now for $18.74
No default payment method selected.
We are sorry. We are not allowed to sell this product with the selected payment method
Pay using card ending in
By confirming your purchase, you agree to Audible's Conditions of Use and Amazon's Privacy Notice. Tax where applicable.
Publisher's Summary
Ready to crank up a neural network to get your self-driving car to pick up the kids from school? Want to add "deep learning" to your LinkedIn profile?
Well, hold on there....
Before you embark on your epic journey into the world of deep learning, there is basic theory to march through first! Take a step-by-step journey through the basics of neural networks and deep learning, made so simple that...even your granny could understand it!
What you will gain from this audiobook:
- A deep understanding of how a neural network and deep learning work
- A basics comprehension on how to build a deep neural network from scratch
Who this audiobook is for:
- Beginners who want to approach the topic, but are too afraid of complex math to start!
What’s inside?
- A brief introduction to machine learning
- Two main types of machine learning algorithms
- A practical example of unsupervised learning
- What are neural networks?
- McCulloch-Pitts' neuron
- Types of activation function
- Types of network architectures
- Learning processes
- Advantages and disadvantages
- Let us give a memory to our neural network
- The example of book writing software
- Deep learning: the ability of learning to learn
- How does deep learning work?
- Main architectures and algorithms
- Main types of DNN
- Available frameworks and libraries
- Convolutional neural networks
- Tunnel vision
- Convolution
- The right architecture for a neural network
- Test your neural network
- A general overview of deep learning
- What are the limits of deep learning?
- Deep learning: the basics
- Layers, learning paradigms, training, validation
- Main architectures and algorithms
- Models for deep learning
- Probabilistic graphic models
- Restricted Boltzmann machines
- Deep belief networks
- Available frameworks and libraries
- TensorFlow
Download now!
©2018 Pat Nakamoto (P)2018 Pat Nakamoto