Machine Intelligence at Google Scale ML APIs, TensorFlow and Cloud ML What we’ll cover What is Neural Network and Deep Learning Machine Learning use cases at Google services Externalizing the power with ML APIs TensorFlow: the open source library for ML TensorFlow in the Wild Distributed training and prediction with Cloud ML What is Neural Network and Deep Learning Neural Network is a function that can learn x n > b? w 1 w n x 2 x 1 Inspired by the behavior of biological neurons How do you classify them? weights bias (threshold) Programmers need to specify the parameters Let’s see how neural network solves the problem The computer tries to find the best parameters A neuron classifies a data point into two kinds Gradient Descent: adjusting the params gradually to reduce errors From: Andrew Ng How do you classify them? What we see What the computer “sees” 28 x 28 gray scale image = 784 numbers input vector (pixel data) output vector (probability) How do you classify them? More neurons = More features to extract Hidden Layers: mapping inputs to a feature space , classifying with a hyperplane From: Neural Networks, Manifolds, and Topology, colah's blog How about this? More hidden layers = More hierarchies of features How about this?