AI & Machine Learning

Ready to learn Machine Learning? Browse Machine Learning Training and Certification courses developed by industry thought leaders and Experfy in Harvard Innovation Lab. I wanted to figure out where I should train my deep learning models online for the lowest cost and least hassle. I wasn’t able to find a good comparison of GPU cloud

Ready to learn Machine Learning? Browse Machine Learning Training and Certification courses developed by industry thought leaders and Experfy in Harvard Innovation Lab. How to parallelize and distribute your Python machine learning pipelines with Luigi, Docker, and Kubernetes   This article presents the easiest way to turn your machine learning application from a simple Python

Ready to learn Machine Learning? Browse Machine Learning Training and Certification courses developed by industry thought leaders and Experfy in Harvard Innovation Lab. Welcome to part five of Learning AI if You Suck at Math. If you missed part 1, part 2, part3, part4, and part5 be sure to check them out. If you’ve followed parts of this series you

Ready to learn Machine Learning? Browse Machine Learning Training and Certification courses developed by industry thought leaders and Experfy in Harvard Innovation Lab. A way to teach Machines how to comprehend Natural Languages. Introduction Humans don’t start their thinking from scratch every second. As you read this essay, you understand each word based on your

Ready to learn Artificial Intelligence? Browse courses like  Uncertain Knowledge and Reasoning in Artificial Intelligence developed by industry thought leaders and Experfy in Harvard Innovation Lab. IT automation is coming and by using AI, it can happen fast. If you think about it, businesses buy electricity, gas and water as utilities, they don’t have people on

A.I. is a rapidly growing industry. A ton of jobs formerly done by people have been outsourced to robots and computers. But there’s no reason to worry, because these losses have been offset by the growth of jobs in A.I. However, to get a job in A.I. you need a fairly impressive skill set, and

Ready to learn Machine Learning? Browse Machine Learning Training and Certification courses developed by industry thought leaders and Experfy in Harvard Innovation Lab. What are the best applications of AI in marketing in 2018?   In the last 10 years, there’s no field where AI has been more consistently applied than in digital marketing. That’s because,

Today, we’re going to write our own Python image recognition program. To do that, we’ll explore a powerful deep learning architecture called a deep convolutional neural network (DCNN). Convnets are the workhorses of computer vision. They power everything from self-driving cars to Google’s image search.  So why are neural networks so powerful? One key reason: They do automatic pattern recognition. So what’s pattern recognition and why do we care if it’s automatic? Patterns come in many forms but let’s take two critical examples: The features that define a physical form.

When we talk about bias we mean the same thing whatever our discipline. Whether we are talking about cognitive bias, social bias, statistical bias or any other sort of bias, bias is an inaccuracy which is systematically incorrect in the same direction. This article will provide enough of a technical intuition about the causes of biases in algorithms, while offering an accessible take on how we are inadvertently amplifying existing social and cognitive biases through machine learning — and what we can do to stop it.

The problem is most guides talk about tensors as if you already understand all the terms they’re using to describe the math. So what is a tensor and why does it flow? At its core it’s a data container. Mostly it contains numbers. Sometimes it even contains strings, but that’s rare. There are multiple sizes of tensors. Let’s go through the most basic ones that you’ll run across in deep learning

The lack of knowledge on what’s actually in the archive will also prevent the company from taking full advantage of the often huge and unexplored goldmine that lies in the archived information and using it as fuel to accelerate and spur on new services and innovations. Businesses ability to‘re-envision’ their data can have a strong impact on the success of any enterprise in the digital transformation race. But how do they get there?