Check out these links where there is some success in processing video with neural networks using a Convolutional Neural Network (CNN) followed by a Recursive Neural Network (RNN) using LSTM’s (Long Short-term Memory) modules.
Convolutional Neural Networks got inspired from the way our human visual cortex works (human eye) and classifies images like dog, cat, man, women, car, jet, or computer.
Convolutional Neural Networks are used for the classification of images.They do a great job because the training of the neural network breaks up the image into component parts and does classification based on various parts of the image. So a dog or cat or numerical number is learned by the various properties of the image. Here are some great links:
best tutorial: Convolutional Neural Networks (CNNs / ConvNets)
Google’s TensorFlow neural networks
Visualizing and Understanding Deep Neural Networks by Matt Zeiler
Visualizing and Understanding Convolutional Networks
Deep Learning Reading List
Google’s TensorFlow: Convolutional Neural Networks
wow, look at the ability for Machine Learning and Artificial Intelligence to learn your music rhythm and melody and play a duet on it.
Try it: Here! How does it work: Here!
It is here based on Google’s TensorFlow Machine Learning open source software. Check out this link about “Make Music and Art Using Machine Learning” at magenta.tensorflow.org Then look at Learning from A.I. Duet . Some real possibilities for expanding music and allowing software to help accompany the musician. Yes this will not make one a better musician, but it sure helps to make more music. The software is part of the work of the Google Brain team who work on Magenta project in collaboration with the Google Creative Lab team.
Now to take this to the next level, consider this note on
Style-conditioned music generation
Piano in the sunlight
With machine learning, Neural Networks are looking promising for deep learning. But there is the rise of Bayesians, which is researchers doing Artificial Intelligence (AI) through the scientific method starting with an hypothesis. There is lots of trial and error designing a Neural Network, lots of parameters to tweak as one tries to get the data to correlate. Can machine learning and neural networks help us design better neural networks?
Great video on Deep Learning and Multilayer Neural Networks, Deep Learning Summer School, Montreal 2015
Visual features: From Fourier to Gabor, Deep Learning Summer School, Montreal 2015
What is a MOOC? — a study course made available over the Internet for free to a large number of people
The Columbia River in the snow
Maybe the top classes in Machine learning and Artificial Intelligence.
Intro to Artificial Intelligence Class Online – Udacity
Artificial Intelligence (AI) – Columbia University
Machine Learning and algorithms – Columbia University
For introductory material on machine learning and neural networks:
Great Google AI Platform: TensorFlow.org – Machine Intelligence
Also look at: Google Cloud Machine Intelligence and Google Cloud Machine Learning
Some AI platforms:
A Tour of Machine Learning Algorithms
Most platforms seem to use python programming language (or c++) for the interface.
- Data Analysis, Data Mining, Machine Learning and Mathematical Modeling are tools.
- Artificial Intelligence — automatic ways of reasoning.
- Machine Learning — turning data in to information and making decisions.
- Data Mining — extracting information from lots of data
- Artificial neural network (ANN)
- Pattern recognition