Despite $200+ billion spent on ML tools, data science teams still struggle to productionize their data and ML models. We decided to do a deep dive and find out why. Back in 1991, former US Air Force pilot and noted strategist John Boyd called for U.S. Military reforms after Operation Desert Storm. He noted that […]
With data being touted as the oil for digital transformation in the 21st century, organizations are increasingly looking to extract insights from their data by building and deploying their custom-built ML models. In our previous article (MLOps – The CEO’s Guide to Productionization of Data, Part 1), we learned why and how embedding ML models […]
MLOps (or Machine Learning Operations) is a core function of Machine Learning engineering, that focuses on streamlining the process of taking ML models to production, and maintaining and monitoring them. But before we get into more details about MLOps, it’s important to understand what operationalization of machine learning is, why it’s important, and how it […]
Over the past 3 years, we’ve heard a lot about Feature Stores. While they might not sound like much, over time, they’ve become table stakes for enterprises building their offerings on ML. The rapid adoption of feature stores, where they’re starting to become mainstream instead of being a niche restricted to big-tech, can largely be […]
Anomaly detection refers to the process of analysing data sets to detect unusual patterns and outliers that do not conform to expectations. It takes on even more importance in a world where enterprises depend heavily on an intricate web of distributed systems. With thousands of potentially important data items to monitor every second, it is […]
As industries across the globe attempt to adapt to the big data architecture, expensive and ineffective feature engineering practices mean that businesses are very likely to “hit a wall” when it comes to organizing their machine learning operations (MLOps). A lot of time is consumed in data ingestion, and lackluster machine outputs indicate that stakeholders […]
The Fintech market is valued at $110.57 billion in 2020 and will reach $698.48 billion by 2030. It is one of the fastest-growing industries with a CAGR of 20.3%. Fintech companies faced a surge in demand as customer practices and banking habits changed during the COVID-19 era. The industry overall saw an increase in user […]
Machine learning and data science today are in a unique position where access to capital is often not the biggest barrier to success. Companies globally are continuing to invest into artificial intelligence to the tune of $140 billion, either to develop AI-native products or solutions or as a way to solve business problems and improve […]
We recently had the good fortune of speaking at ValleyML’s AI Expo 2022 earlier this month. This is an annual event that presents a unique combination of AI Technology, researchers, industry thought leaders and prospective buyers of AI/ML technologies in a single event. The 2022 edition promised even more interesting talks and networking opportunities as it spanned four […]
The data privacy and compliance landscape continues to significantly change in 2022, and it is necessary to understand these changes as soon as possible so you can chart your path, and that of your organization, over the next few years. EMERGING MEGATRENDS IN THE WORLD OF DATA 01. Increased regulatory activity. In the last couple […]
