DM Wk3 Discussion
alakhbiniwale
Chapter6_AnalyticsDataScienceArtificialIntellience.pptxAnalytics, Data Science, & Artificial Intelligence, 11th Edition
Chapter 6 Slides
Opening Example
Opening Vignette
Danske Bank
Results
Realize a 60 percent reduction in false positives with an expectation to reach as high as 80 percent.
Increase true positives by 50 percent.
Focus resources on actual cases of fraud.
Introduction to Deep Learning
Deep learning with AI-based learning
Process of developing neural network-based systems
Review Figure 6.11
Learning process in ANN
Supervised learning
Performance function
Over-fitting
Illuminating the black box of Ann
Deep Neural Networks
Convolution Neural Networks
Pooling
Convolution Network unit
Recurrent networks and long short-term memory networks
RNN- specifically designed to process sequential inputs. An RNN basically models a dynamic system where (at least in one of its hidden neurons) the state of the system (i.e., output of a hidden neuron) at each time point t depends on both the inputs to the system at that time and its state at the previous time point t - 1.
Computer frameworks for implementation of deep learning
Torch
Caffe
TensorFlow
Theano
Figure 6.36
Cognitive computing
Wrap Up
Review the Chapter highlights
Review the key terms
Complete the weekly homework
