In Neural Network Programming with TensorFlow training course, you will learn to create a handwritten number recognition system trained on the famous MNIST dataset, work with simple multilayer perceptron to a state of the art Deep Convolutional Neural Network.
By attending Neural Network Programming with TensorFlow Workshop, delegates will learn to:
- Develop a strong background in neural network programming from scratch, using the popular Tensorflow library
- Use TensorFlow to implement different kinds of neural networks - from simple feedforward neural networks to multilayered perceptrons, CNNs, RNNs and more
- Explore Optimization techniques for solving problems like Local minima, Global minima, Saddle points
- Understand the Linear Algebra and mathematics behind neural network
This Neural Network Programming with TensorFlow class is meant for developers with a statistical background who want to work with neural networks. Though we will be using TensorFlow as the underlying library for neural networks, the course can be used as a generic resource to bridge the gap between the math and the implementation of deep learning.