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Michael Abramov

Michael Abramov

3 Ways to Improve Performance of ML Models

3 Ways to Improve Performance of ML Models

The ultimate goal of technology has always been to mimic the human brain. The rapidly expanding field of artificial intelligence aims to do just that. But what factors allow AI to make sense of the world accurately? To answer that question, we need to discuss machine learning model performance. Machine

How to Label Datasets for Machine Learning

How to Label Datasets for Machine Learning

In the world of machine learning, data is king. But data in its original form is unusable. That’s why more than 80% of each AI project involves the collection, organization, and annotation of data. The “race to usable data” is a reality for every AI team — and, for many,

How Image Annotation Projects Transform Waste Management

How Image Annotation Projects Transform Waste Management

Artificial intelligence has revolutionized industries. But while most people have heard of self-driving cars and facial recognition software, many of us are unaware of the enormous impact AI has had for the waste management and recycling sectors. Imagine a waste management facility. Are you picturing rows of machines? That’s

Polygon Image Annotation for Computer Vision

Polygon Image Annotation for Computer Vision

In the field of artificial intelligence, machine learning images and computer vision are becoming one of the hottest subfields at the moment. There are many applications of artificial intelligence and machine learning beyond the development of driverless cars and unmanned drones. In the near future, computer vision and image annotation

AI vs. Deep Learning vs. Machine Learning: What's the

AI vs. Deep Learning vs. Machine Learning: What's the Difference?

Artificial intelligence is the future. Movies and TV shows like Ex Machina, The Terminator, Westworld, and Her paint a world that’s eerily similar to our own, in which machines can do everything humans can, and more — infinitely more. But AI is an umbrella term. And its applications extend far

Instance vs. Semantic Segmentation: What Are the Key Differences?

Instance vs. Semantic Segmentation: What Are the Key Differences?

Computer vision applications are endless. The field of computer vision implementation is from self-driving vehicles to robust facial recognition software. Computer vision is one of the hottest subfields of AI at the moment. But human vision has proven itself as a uniquely challenging gift to bestow on machines. As living

5 Reasons You Need to Outsource Image and Video

5 Reasons You Need to Outsource Image and Video Annotation

We take our vision for granted. While navigating and understanding the visual world around us is a simple task, even for children, training computers to do the same is far from simple. And yet, countless large tech companies and startups are heavily investing in machine learning and AI. With computer