Web Class: Introduction to Cluster Analysis with Python

Transcript Part 1 Hello, world, and thanks for joining me. My name is Mohit Deshpande. In this course, we’ll be learning about clustering analysis. In particular, we’re gonna use it in the context of data science, and we’re gonna analyze some data and see if we can segment out different kinds of customers so that … Read moreWeb Class: Introduction to Cluster Analysis with Python

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 Ebook – Machine Learning For Human Beings

Machine Learning Fundamentals

We are excited to announce the launch of our free ebook Machine Learning for Human Beings, authored by researcher in the field of computer vision and machine learning Mohit Deshpande, in collaboration with Pablo Farias Navarro, founder of Zenva. In over 100 pages you will learn the basics of Machine Learning – text classification, clustering and even face recognition … Read moreFree Ebook – Machine Learning For Human Beings

Dimensionality Reduction

Dimensionality Reduction is a powerful technique that is widely used in data analytics and data science to help visualize data, select good features, and to train models efficiently. We use dimensionality reduction to take higher-dimensional data and represent it in a lower dimension. We’ll discuss some of the most popular types of dimensionality reduction, such … Read moreDimensionality Reduction

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

Clustering with Gaussian Mixture Models

Clustering is an essential part of any data analysis. Using an algorithm such as K-Means leads to hard assignments, meaning that each point is definitively assigned a cluster center. This leads to some interesting problems: what if the true clusters actually overlap? What about data that is more spread out; how do we assign clusters then? … Read moreClustering with Gaussian Mixture Models

Data Clustering with K-Means

Determining data clusters is an essential task to any data analysis and can be a very tedious task to do manually! This task is nearly impossible to do by hand in higher-dimensional spaces! Along comes machine learning to save the day! We will be discussing the K-Means clustering algorithm, the most popular flavor of clustering … Read moreData Clustering with K-Means

A Guide to Improving Deep Learning’s Performance

Although deep learning has great potential to produce fantastic results, we can’t simply leave everything to the learning algorithm! In other words, we can’t treat the model as some black-box, closed entity that can read our minds and perform the best! We have to be involved in the training and design process to make sure … Read moreA Guide to Improving Deep Learning’s Performance

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