In the era of digital transformation, smart technologies are revolutionizing most industries, and the manufacturing

Once you start collecting data to train classification models in machine learning, you might notice

Heavy equipment is mainly used extensively in industries such as construction, oil and gas, mining,

Modern security operations essentially rely heavily on the data that the security devices record. However,

“AI is the new electricity” – Andrew Ng (Entrepreneur and Co-founder of Google Brain) The

The fleet industry has faced challenges related to operational inefficacies, theft, fleet maintenance since time immemorial. Today AI is helping to solve these and other persistent problems of the industry. Is it possible to eliminate these challenges completely? Perhaps not, but with AI-powered solutions, it is possible to face these with greater efficiency.

When trying to gain business value through machine learning, access to best hardware that supports all the complex functions is of utmost importance. With a variety of CPUs, GPUs, TPUs, and ASICs, choosing the right hardware may get a little confusing. This blog discusses hardware consideration when building an infrastructure for machine learning projects.

What influences the customer buying decision for any product that they do not actually need?

Within the production pipeline, we want our machine learning applications to perform well on unseen data. It doesn’t really matter how well an ML application performs on training data if it cannot deliver accurate results on test data. To achieve this purpose, we use regularization techniques to moderate learning so that a model can learn instead of memorizing training data.