Creating Custom TensorFlow Dataset

Creating Custom TensorFlow Dataset

In the previous article, we had a chance to see how one can scrape images from the web using Python. Apart from that, in one of the articles before that we could see how we can perform transfer learning with TensorFlow. In that article, we used famous Convolution...
Introduction to Chatbots and Their Business Value

Introduction to Chatbots and Their Business Value

In today’s world, the majority of businesses have some sort of an e-shop or are e-commerce oriented (meaning: good portion of business can be done online). However, what if your Customer has an issue, and she/he needs to contact the Support, and it is outside of your...
Transfer Learning with TensorFlow 2 – Model Fine Tuning

Transfer Learning with TensorFlow 2 – Model Fine Tuning

In the previous article, we had a chance to explore transfer learning with TensorFlow 2. We used several huge pre-trained models: VGG16, GoogLeNet and ResNet. These architectures are all trained on ImageNet dataset and their weights are stored. We specialized them for...
Transfer Learning with TensorFlow 2

Transfer Learning with TensorFlow 2

It is always fun and educational to read deep learning scientific papers. Especially if it is in the area of the current project that you are working on. However, often these papers contain architectures and solutions that are hard to train. Especially if you want to...
Business Value of Artificial Intelligence

Business Value of Artificial Intelligence

As you may already know, the amount of data that we create, and store, as human beings has been growing immensely in the last few years. We start having more and more devices that can create, send, store and save data – we can just look at our mobile phones, and how...
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!