An Introduction to Machine Learning

An Introduction to Machine Learning

You can access the full course here: Machine Learning for Beginners with TensorFlow Intro to Machine Learning Now that we know what the course is all about, let’s learn a bit about the main topic: machine learning. What is machine learning? Machine learning is the study of statistics and algorithms aimed at performing a task … Read more An Introduction to Machine Learning

How to do Cluster Analysis with Python

You can access the full course here: Data Insights with Cluster Analysis Part 1 In this video we are going to discuss Cluster Analysis. We will discuss the following topics: Intro to Cluster Analysis – what is it, what are it’s different applications, the kinds of algorithms we can expect. K-means clustering Density-based Spatial Clustering … Read more How to do Cluster Analysis with Python

A Comprehensive Guide to Neural Networks

You can access the latest Machine Learning courses here: Machine Learning Mini-Degree Transcript 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 … Read more A Comprehensive Guide to Neural Networks

The Complete Programming and Full-Stack Bundle – 20 Course Smart Curriculum

?? Go from beginner to full-stack developer! The Complete Programming and Full-Stack Bundle is the world’s most effective way to go from beginner to professional coder. Whether your goal is to advance your career, start your own business or expand your existing skill-set, our 20-course Smart Curriculum has something in store for you. This bundle is suitable both … Read more The Complete Programming and Full-Stack Bundle – 20 Course Smart Curriculum

An Introduction to AI

You can access the full course here: The Complete Artificial Neural Networks Developer Course Why do we even have artificial intelligence? Computers are really dumb machines! When we write code and programs, we give the computer a very explicit set of instructions that it isn’t allowed to deviate from. Inside of our program, we must … Read more An 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 more Free 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 more Dimensionality 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 more All 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 more Face 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 more Clustering with Gaussian Mixture Models