Web Class: An Introduction to Neural Networks

Transcript Part 1 Hello everybody. My name is Mohit Deshpande. And before we get into our main topic of neural networks, I first wanna talk a little bit about where they come from. In this video, I just wanna very briefly just go over kind of the inspiration for neurons, and this topic of neural … Read moreWeb Class: An Introduction to Neural Networks

Web Class: Introduction to AI

Transcript In this video I just need to introduce the concept of what artificial intelligence and machine learning to then help give some background information. So first of all what is artificial intelligence and why do we actually need it? And so to kind of think of this case, you have to accept the fact that the computers are actually really dumb … Read moreWeb Class: Introduction to AI

Free E-book – Deep Learning with Python for Human Beings

We are excited to announce that we have just released a comprehensive new intermediate-level eBook on Machine Learning! Written by computer science researcher Mohit​ ​Deshpande, this eBook is guaranteed to give you that more advanced outlook in this exciting field. The concepts covered in this book build on top of our previous entry-level Machine Learning … Read moreFree E-book – Deep Learning with Python for Human Beings

Recurrent Neural Networks for Language Modeling

Many neural network models, such as plain artificial neural networks or convolutional neural networks, perform really well on a wide range of data sets. They’re being used in mathematics, physics, medicine, biology, zoology, finance, and many other fields. However, there is one major flaw: they require fixed-size inputs! The inputs to a plain neural network … Read moreRecurrent Neural Networks for Language Modeling

All About Autoencoders

Data compression is a big topic that’s used in computer vision, computer networks, computer architecture, and many other fields. The point of data compression is to convert our input into a smaller representation that we recreate, to a degree of quality. This smaller representation is what would be passed around, and, when anyone needed the original, they … Read moreAll About Autoencoders

Face Recognition with Eigenfaces

Face recognition is ubiquitous in science fiction: the protagonist looks at a camera, and the camera scans his or her face to recognize the person. More formally, we can formulate face recognition as a classification task, where the inputs are images and the outputs are people’s names. We’re going to discuss a popular technique for face … Read moreFace Recognition with Eigenfaces

Introduction to Convolutional Neural Networks for Vision Tasks

Neural networks have been used for a wide variety of tasks across different fields. But what about image-based tasks? We’d like to do everything we could with a regular neural network, but we want to explicitly treat the inputs as images. We’ll discuss a special kind of neural network called a Convolutional Neural Network (CNN) that … Read moreIntroduction to Convolutional Neural Networks for Vision Tasks

Complete Guide to Deep Neural Networks – Part 2

Read Part 1 here. Last time, we formulated our multilayer perceptron and discussed gradient descent, which told us to update our parameters in the opposite direction of the gradient. Now we’re going to mention a few improvements on gradient descent and discuss the backpropagation algorithm that will compute the gradients of the cost function so … Read moreComplete Guide to Deep Neural Networks – Part 2

Complete Guide to Deep Neural Networks – Part 1

Neural networks have been around for decades, but recent success stems from our ability to successfully train them with many hidden layers. We’ll be opening up the black-box that is deep neural networks and looking at several important algorithms necessary for understanding how they work. To solidify our understanding, we’ll code a deep neural network … Read moreComplete Guide to Deep Neural Networks – Part 1

Perceptrons: The First Neural Networks

Neural Networks have become incredibly popular over the past few years, and new architectures, neuron types, activation functions, and training techniques pop up all the time in research. But without a fundamental understanding of neural networks, it can be quite difficult to keep up with the flurry of new work in this area. To understand … Read morePerceptrons: The First Neural Networks

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