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How Machine Learning can transform Data Centers and their Management Strategies

We often hear of the use of machine learning in risk analysis. Within the data center industry developers are only beginning to discover the...

How AI & Machine Learning Are Changing The Future Of Customer Service Forever

The pace of change cannot be determined, and that’s the reason why business executives are seen keeping a pulse on emerging trends...

6 Surefire Ways to Land Rewarding Freelance Job in AI

Everyone seems to talk about how Artificial Intelligence (AI) is coming for their jobs, and that freelancers will probably be worst hit,...

Learning Natural Selection in the Human Genome with Machine Learning

Machine learning today is being used in the medical field quite regularly. Having an exact pinpoint of how our genome as a whole is...

AI-Powered Digital Asset Management (DAM)—What It Is and How It Works

They say that content is king. However, it’s the kind of king you want to control and use as an asset in...

China’s AI-Led New Retail Environment – Everything You Should Know

China’s booming economy is powering its retail industry's growth.From e-commerce, the industry is now moving towards “New Retail” and integrating fast-evolving technologies...

Will Machine Learning Enable Time Travel?

Traveling in time has always been a dream of mankind. Imagine being able to experience ancient Rome first hand or to...

Are Self-Service Machine Learning Models the Future of AI Integration?

For some years, Artificial Intelligence (AI) and Machine Learning (ML) becoming part and parcel of modern business solutions. While both of these...

Introduction to Image Classification using Pytorch to Classify FashionMNIST Dataset

In this blog post, we will discuss how to build a Convolution Neural Network that can classify Fashion MNIST data using Pytorch on Google Colaboratory. The way we do that is, first we will download the data using Pytorch DataLoader class and then we will use LeNet-5 architecture to build our model. Finally, we will train our model on GPU and evaluate it on the test data.

Deep Learning could help us produce a faster Cardiac MRI’s Report

Researchers today are using deep learning algorithms to almost instantly quantify data and produce fast reports with cardiac MRIs. With the assistance of artificial...
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