...
Full Bio
Whats powers the future of Artificial Intelligence?
2 days ago
How can Big Data improve Healthcare Industry?
2 days ago
Every Beginner should focus on these Machine Learning books
2 days ago
Bitcoin: Future
5 days ago
Data Science: Can everybody pursue it?
5 days ago
Every Programmer should strive for reading these 5 books
547233 views
Why you should not become a Programmer or not learn Programming Language?
198414 views
See the Salaries if you are willing to get a Job in Programming Languages without a degree?
144000 views
Highest Paid Programming Languages With Highest Market Demand
126171 views
Python Programming Language can easily be acquired easily. How?
114636 views
Learn Deep Learning (Neural Networks) Models from scratch
- Understand the major technology trends driving Deep Learning
- Be able to build, train and apply fully connected deep neural networks
- Know how to implement efficient (vectorized) neural networks
- Understand the key parameters in a neural network's architecture
- describe what a neural network is, what a deep learning model is, and the difference between them.
- demonstrate an understanding of unsupervised deep learning models such as autoencoders and restricted Boltzmann machines.
- demonstrate an understanding of supervised deep learning models such as convolutional neural networks and recurrent networks.
- build deep learning models and networks using the Keras library.
- Understand how to build a convolutional neural network, including recent variations such as residual networks.
- Know how to apply convolutional networks to visual detection and recognition tasks.
- Know to use neural style transfer to generate art.
- Be able to apply these algorithms to a variety of images, videos, and other 2D or 3D data.