Feature Engineering For Machine Learning: The Ultimate Guide

Almost all industries use artificial intelligence (AI) and machine learning (ML) today. As part of the so-called disruptive technologies, they've upended current technologies and have affected people in the way they work, do business, and spend their leisure time. And, with the pace these techs are advancing, they'll continue to be at the forefront of technological progress in the next few years.

How Real Estate Investors Can Use Artificial Intelligence

How do you determine whether one multifamily deal is better than another? Let me start by saying that a deal is only as good as the assumptions you’re making as an investor, and assumptions are not guaranteed to materialize. As a real estate investor, operator and syndicator through my company Blue Lake Capital, a significant part of our analysis when considering properties to invest in is looking at how the property performed in the past.


5 AI Use Cases in ITSM and ITOM

A broad enthusiasm for AI is already evidenced by the technology’s adoption within many organizations in 2021. In a recent multinational survey conducted by IDG, we found that more than one-quarter (27%) of the survey respondents have fully deployed AI-enabled ITSM/ITOM solutions, and another 34% have made initial deployments in select use cases and departments. At the same time, another 32% are exploring AI-based solutions or gathering information about them.


What Are the Limitations of Dashboards?

For modern businesses faced with increasing volumes and complexity of data, it’s no longer efficient or feasible to rely on analyzing data in BI dashboards. Traditional dashboards are great at providing business leaders with insights into what’s happened in the past, but what if they need actionable information in real time? What if they want to use their data to estimate what may happen in the future? Companies are taking notice.


Interview with AI Specialist Dhonam Pemba

For our latest expert interview on our blog, we’ve welcomed Dhonam Pemba to share his thoughts on the topic of artificial intelligence (AI) and his journey behind founding KidX AI. Dhonam is a neural engineer by PhD, a former rocket scientist and a serial AI entrepreneur with one exit. He was CTO of the exited company, Kadho which was acquired by Roybi for its Voice AI technology. At Kadho Sports he was their Chief Scientist which had clients in MLB, USA Volleyball, NFL, NHL, NBA, and NCAA.

ManageEngine Insights - Fireside Chat on "Decoding the power of enterprise AI"

Artificial intelligence is becoming increasingly powerful and ubiquitous. This coupled with the rapid pace of AI adoption has many organizations scrambling to adopt some form of enterprise AI. However, many experts also believe that while AI adoption has accelerated in recent times, it may be moving too fast. In a bid not to get left behind, many organizations jump onto the AI bandwagon without fully understanding how it fits in with their organizational strategy. Many business leaders also believe that some level of control and regulations is required to ensure AI solutions achieve their full potential.

What is a decision support system in artificial intelligence (AI)?

Most companies today have no trouble gathering data, but knowing what to do with that data is the tricky—and time-consuming—part. Even brilliant organizations are challenged with making smart business decisions after thorough data analysis. Bridging the gap between data analytics and decisions is where a decision support system (DSS) is incredibly useful.


Increase approval rates with AI-based payment transaction monitoring

The financial world is being increasingly digitized and decentralized with many more networks, data sources and movements that need to be reconciled and monitored — not to mention satisfy compliance requirements with various regulatory bodies. The digital transformation and decentralization of the Fintech segment has resulted in increasing channel complexities, more third party applications and a higher volume and velocity of payments data that need to be monitored in real-time.

Empower Your Network Operations Team With AI

Voice networks are become increasing complex. Unfortunately, most businesses do not have the luxury of having vast multi-domain expertise within their voice network teams to address the all of new operational challenges that comes with SIP, Cloud Architectures, Multi-Access Networks, Policy and Routing, and so on. That overwhelming complexity inherently is driving the need for different types solutions to ensure efficient operations.