Machine Learning

Managing Machine Learning Workloads Using Kubeflow on AWS with D2iQ Kaptain

While the global spend on artificial intelligence (AI) and machine learning (ML) was $50 billion in 2020 and is expected to increase to $110 billion by 2024 per an IDC report, AI/ML success has been hard to come by—and often slow to arrive when it does. There are four main impediments to successful adoption of AI/ML in the cloud-native enterprise.

How to build a data science and machine learning roadmap in 2022

Closing the gap between their organization’s choice to invest in a data science and machine learning (DSML) strategy and the needs that business units have for results, will dominate data and analytics leaders’ priorities in 2022. Despite the growing enthusiasm for DSML’s core technologies, getting results from its strategies is elusive for enterprises.

Eight Effective Ways To Leverage Machine Learning Ad Tools

More and more agencies and brands are relying on machine learning these days to analyze mountains of data and provide insights they can use to better inform advertising campaigns. Using ML, artificial intelligence tools can recognize patterns in data gleaned from existing campaigns to see how ads are impacting customer engagement, purchase intent and conversion rates.

AI and machine learning in compliance technology

It’s true that AI and machine learning have already provided us with some opportunities to transform entrenched methods of recording and monitoring communications in regulated industries. However, to date, most companies’ injection of AI has been limited and solutions have been piecemeal. But that’s all about to change as the rapid expansion in the applications of AI in compliance is just around the corner.

How AI and ML will impact the future of software development with Nathan Mellis

Rob sits down with Nathan Mellis, Director of Engineering at Modzy to discuss all things ML and AI in the space of software development. Get answers to questions like, Join this fascinating conversation of where the industry of software development is headed next.

Top 5 Machine Learning Trends to Look Out For in 2021

Almost everyone nowadays understands what machine learning is. Some of the most exciting machine learning trends in the coming years have the potential to completely transform our current social, industrial, and economic structures. Furthermore, the machine learning industry is rapidly expanding, opening up a plethora of opportunities for business expansion.

Machine Learning for the Financial Sector using D2iQ's Kaptain

Learn how your Financial organization can benefit from Kubernetes with machine learning. Kaptain, D2iQ's cloud-native end-to-end machine learning platform, already powers government organizations and research teams across the globe in highly secure environments. Financial organizations can now leverage that same technology to infuse their products and services with AI.

Understand the scope of user impact with Watchdog Impact Analysis

Watchdog is Datadog’s machine learning and AI engine, which leverages algorithms like anomaly detection to automatically surface performance issues in your infrastructure and applications. Without any manual setup or configuration, Watchdog generates a feed of Alerts—on anomalies such as latency spikes, elevated error rates, and network issues in cloud providers—to help you reduce your mean time to detection.

How Artificial Intelligence And Machine Learning Are Transforming The Future Of Renewable Energy

We use energy in many different ways in our lives, be it for lighting up our houses, running electronic appliances or as fuel in our vehicles. There are mainly two types of energy: renewable energy and non-renewable energy. Non-renewable energy includes fossil fuels like natural gas, petroleum and coal. However, these energy sources come from nature itself; it is impossible to renew them quickly. This means that these resources will become entirely exhausted in the upcoming years.

Achieve Breakthrough Performance in Your Microsoft Environment

In a world where 1.145 trillion MB of data is generated every day, the art of database management has become more important than ever. I use the word “art” because it captures a sense of the wizardry needed to effectively manage data. After all, our world is dominated by mobile devices and hybrid IT environments. Database migrations happen regularly, and data resides both on-premises and in the cloud. All these things have brought a new complexity to database management.