Introduction to Transformers Architecture
In this article, we explore the interesting architecture of Transformers, a special type of sequence-to-sequence models used for language modeling, machine translation, etc.
Deep Convolutional Q-Learning with Python and TensorFlow 2.0
Now, if there is something that data scientists like to do, is merge concepts and create new beautiful and unexpected models. That is why in this article, we will find out what happens when we give the learning agent ability to “see”, i.e. what happens when we involve convolutional neural networks into Deep Q-Learning framework.
Guide to Machine Learning with ML.NET 1.0
As a person coming from .NET world, it was quite hard to get into machine learning right away. One of the main reasons was the fact that I couldn't start Visual Studio and try out these new things in the technologies I am...
TO-DO or not TO-DO
This is a guest post by Ana Marija Ćirić. Have you ever gone to the grocery store with a shopping list of 3 items in your mind thinking you don’t have to write those 3 things down because it’s simple enough to keep them in your...
Introduction to Q-Learning with Python and Open AI Gym
The code that accompanies this article can be downloaded here. In the previous article, we got familiar with reinforcement learning and the problem it is trying to solve. Reinforcement learning is the third paradigm or...
Agile Database Development Best Practices
This is a guest post by Gilad David Maayan. Over the last decade, we have witnessed the growing need for quality, agility, and speed in the field of application code development. To meet this demand, organizations are adopting...
Introduction to Reinforcement Learning
Edward observed his cats as they tried to escape from home-made puzzle boxes. Puzzles were simple, all cats had to do was pull some string or push a poll and they were out. When first encountered with a puzzle cats took a long...
Guide to Exploratory Data Analysis with Python
The crucial part of any machine learning, deep learning application and artificial intelligence application is data. You might have heard the term “garbage in – garbage out” that is often used by the more experienced data scientist. In this article, we are going to explore ways to find “garbage” in your data.
Mathematics for Artificial Intelligence Series
Machine Learning, Neural Networks and Artificial intelligence are big buzzwords of the decade. It is not surprising that today these fields are expanding pretty quickly and are used to solve a vast amount...
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