There are times when it’s extremely useful to figure out the underlying structure of a data set. Having access to the most important data features gives you a lot of flexibility when you start applying labels. Autoencoders are an important family of neural networks that are well-suited for this task.… Continue Reading Autoencoders – Ep. 10 (Deep Learning SIMPLIFIED)

– If I asked you to have a guacamole party with me, would you do it? If she would say yes, then the bot would smile and playfully say okay do women love anything more than avocados? (suspenseful music) Oftentimes when there were dull evenings, I would try to find… Continue Reading How HACKERS Are Using AI & Facial Recognition on Tinder | Mashable Originals

Welcome back, today I got a different sort of Stop-Motion video for you: A video straight from the state-of-the-art of AI research. If you’re a Stop-Motion animator, like me, you probably know the effort it takes to record movies at 30, let alone 60 frames per second. I personally stick… Continue Reading Boosting Stop Motion Animations to 60 fps using AI

If you want a high-quality deep learning library with plenty of great extensions and the support of a large community, then you should take a look at Torch. Torch offers GPU support, the option to set up a deep net by configuring its hyper-parameters, and many other useful features. Let’s… Continue Reading Torch – Ep. 19 (Deep Learning SIMPLIFIED)

One of the goals of Big Data Analytics is to make the most out of the mountains of unstructured textual data we have access to. Standard Natural Language Processing techniques are okay, but Deep Learning can truly revolutionize the field of text analytics. In this video, we’ll explore the key… Continue Reading Text Analytics – Ep. 25 (Deep Learning SIMPLIFIED)

There are so many important use cases for Deep Learning, that it’s impossible to produce an exhaustive list. Deep Learning is just getting started, and new applications pop up all the time. Let’s take a look at some of the biggest ones today. At this point, it should be no… Continue Reading Use Cases – Ep. 12 (Deep Learning SIMPLIFIED)

Okay, so an RBM can extract features and reconstruct inputs…but how exactly does that help with the vanishing gradient? By combining RBMs together and introducing a clever training method, we obtain a powerful new model that finally solves our problem. Let’s now take a look at a Deep Belief Network.… Continue Reading Deep Belief Nets – Ep. 7 (Deep Learning SIMPLIFIED)

How do we learn? Although times may change, some concepts stay the same. Unchanging, information outlasts the body. It’s stored in our brain, but can be passed down from generation to generation. Our brain is capable of synthesizing the diverse set of inputs we call our five senses, and from… Continue Reading How to Make a Neural Network – Intro to Deep Learning #2

Let’s continue with the Blocky puzzle challenge. We identified a packet sent from the server to the client that contains the state of the input buttons, 32bits and the state of all the output lines. We then used the proxy to inject random input states and collect a lot of… Continue Reading Failing at Machine Learning (Blocky part 2) – Pwn Adventure 3