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.
Some machine learning or deep learning data sets can take a lot of CPU time, their doing a lot of matrix arithmetic operations. There is a lot of number crunching here.
If you want to write code for GPUs then I suggest you to try the following Udacity course. Introduction to Parallel Programming With CUDA
So the abbreviations are crazy, CPU stands for central processing unit, GPU means graphics processing unit. What is more crazy is that almost all computers have a CPU and a GPU. The CPU does almost all computing to run the various applications (programs) on the computer. The GPU runs the graphics card, but not all GPU’s are easy to use for math calculations beside its graphics.
Then Google is working on a variety of custom machine learning chips that are even faster.
just a snowblower, not a CPU or GPU.
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