From Reactive to Proactive: AI Predictive Testing in Software Development
The old rhythm of software testing—write code, run tests, fix bugs—doesn’t hold up anymore. Continuous releases, sprawling microservices, and unpredictable user behavior are stretching QA teams beyond…
Machine Learning as a Service: What and How to Use It?
Explore what Machine Learning as a Service (MLaaS) is, how it works, and how businesses can leverage it for fast, scalable AI deployments
[Infoblog] AI/ML Intelligence for Digital Innovation
You may also want to take a look at how Calsoft helped an organization with an automation framework for product engineering of their ML system.
AI & Retail: What’s Lined Up for a Post-Pandemic World
E-commerce platforms are currently adopting a cautious approach to the situation and focusing on delivering essentials – though things are currently erratic as everyone is waiting for the crisis to tide over.
Extending a Ticket Analyzer for AI-based Alert Management in Various IoT Domains
For quite some time now, data scientists and machine and deep learning (ML/DL) experts are using different techniques to automate triaging and analysis of tickets in various hi-tech sectors.
[Infoblog] Machine Learning
Machine Learning, or ML as we call it, is not a new entity. Often, ML and Artificial Intelligence (or AI) are used interchangeably as if they are the same terms. But that’s not the case. You’ll see why through this discerning InfoBlog.
Biomedical Image Analysis and Machine Learning
These techniques help in the understanding of the disease as well as initiation and evaluation of ongoing treatment. Apart from this, the dataset of these images is used in further analysis of such diseases occurring around the world as a whole.
Understanding Supervised Machine Learning
Machine learning is about using data to build intelligent artefacts that learn over time. It involves collecting and analysing large amounts of data to extract information using various computational structures and algorithms.
Storage Analytics is becoming more complex – can AI and ML help?
Physical servers and storage equipment are a data center reality. How can we ensure that the workloads are distributed correctly across this infrastructure?AI and Machine Learning can come to the rescue here as well. With these technologies, data centers can distribute workloads equally and efficiently across these servers.
Where AI and ML Meet – and where they diverge
Simple explanations of Machine Learning and Artificial Intelligence, and how they’re related… but not at all the same thing.