Restricted Boltzmann Machine Series

Restricted Boltzmann Machine Series

The path to learning story of Restricted Boltzmann Machine is bumpy. First, we needed to learn what are Energy-Based Models, the group of machine learning models that Restricted Boltzmann Machine is a part of. Then we need to explore functionalities of vanilla...
Self- Organizing Maps Series

Self- Organizing Maps Series

So far in our artificial neural network series, we have covered only neural networks that are using supervised learning. To be more precise, we only explored neural networks that have input and output data available to them during the learning process. Based on this...
Asynchronous Programming in .NET Series

Asynchronous Programming in .NET Series

Asynchronous programming was incorporated into .NET a long time ago. To be more exact, asynchronous programming was introduced with 4.5 version of .NET. That happened on August 15th, 2012. Yes, six years ago. Yes, more than half a decade ago. Apart from sending me...
Machine Learning with ML.NET Series

Machine Learning with ML.NET Series

It’s been more than sixty years since Alan Touring proposed an idea about ‘learning machine’ that could learn and become artificially intelligent. A lot had happened since then. Machine Learning and Artificial Intelligence as concepts went through a...
Deep Learning for ProgrammersLearn how to use software development experience to become deep learning superstar!
  • Why should you care about deep learning?
  • Learn just enough math to be dangerous.
  • Get familiar with Python and TensorFlow.
  • Use familiar paradigms like Object Oriented Programming to understand main Deep Learning concepts.
  • Explore and implement 12 neural network architectures.
  • Solve various real-world problems with neural networks.
  • Learn how to generate images with neural networks.
GO!