A Selective Overview of Deep Learning

Mathematics

• Learning 66%
• Neural Nets 28%
• Drop out 13%
• Stochastic Gradient 13%
• Learning Theory 13%
• Natural Language 13%
• Gradient Descent 12%
• Neural Network Model 12%
• Computer Vision 12%
• Batch 11%
• Training 10%
• Nonlinear Function 10%
• Normalization 10%
• Statistical method 10%
• Neural Networks 9%
• History 9%
• Performance 6%
• Model 3%

Business & Economics

• Deep Learning 100%
• Neural Nets 27%
• Neural Networks 21%
• Natural Language Processing (NLP) 12%
• Computer Vision 12%
• Drop out 11%
• Normalization 10%
• Gradient 9%
• Batch 9%
• Network Model 9%
• Statistical Methods 9%
• Performance 3%