For a more technical explanation on neural networks, refer to one of my older posts.
With the explosion of AI across all industries, Deep Learning has been responsible for many of the major breakthroughs. But for people in non-tech, what exactly is Deep Learning?
Deep Learning is a series of machine learning models based on artificial neural networks.
Okay, we just described what is Deep Learning. However, the definition doesn't define what exactly is an artificial neural network (ANN).
by Joseph Woolf
Earlier this week, I attended the O'Reilly AI Conference up in San Jose, CA. Wednesday and Thursday started off with keynotes showcasing what companies were currently researching in the field of AI. While I'm no expert in the field, I found four key takeaways from the keynotes.
In part 1, I used OpenCV and Python to load our game and get to the board data. In part 2, I built the basic mechanics for our AI to make moves.
In this post, I'll be going over more advanced mechanisms used to allow our AI to make better moves.
In my previous post, I was able to get our code to get past the loading screen and get the board information. However, a program that can only grab the board without acting on the information does no good. In this post, we'll be adding the basic mechanisms for our AI to act on the board information. Please note that more intelligent behavior won't be added in this post.
With the rise of Siri, Google Home, Alexa, and Cortana, it's obvious that there's a demand for chatbots. In the past, chatbots were more of a niche technology due to limited functionality. With recent advancements in computer technology, chatbots have now become practical for everyday use.