The iMerit Blog
From casual to cultured, the iMerit blog tackles a wide array of topics related to security, expertise, and flexibility in the Artificial Intelligence and Machine Learning data-enrichment marketplace.
Feb 6, 2025
Adapting DMS Technology to Handle Unstructured Traffic and Diverse Behavior
Discover how Driver Monitoring Systems (DMS) enhance road safety in India by detecting driver fatigue, distraction, and drowsiness. Learn about AI-powered DMS, its adoption challenges, and its impact on unstructured traffic.
Oct 12, 2022
From Supervised to Unsupervised – The Evolving Role of Training Data in Machine Learning
Learn the steps involved in developing a machine learning model and the distinction between supervised and unsupervised learning.
Oct 7, 2022
Data Annotation Companies – Building the Foundations of Future AI
Learn about the role of data annotation in enabling AI, the different approaches to data annotation, and the outlook for data annotation companies in 2022.
Sep 23, 2022
Training Data in Machine Learning: What’s the Point?
This post is intended to serve as a guide for those data scientists who want to ensure their supervised learning algorithm avoids common ML pitfalls.
Sep 14, 2022
AI Systems for Advanced Diagnostic Radiology: Key Takeaways
In a special guest feature with Healthcare Radius, Dr. Jaideep Jesson Rayapudi, Sr. SME – Healthcare AI at iMerit, highlights
Sep 14, 2022
5 Steps To Implementing AI Solutions: Key Takeaways
When trying to solve any problem with AI, it’s important to consider guidelines, resources, tools, and partners that can help
Sep 7, 2022
Role of Automation in Complex Data Annotation: Key Takeaways
Data annotation plays a key role in making sure AI or ML projects are scalable. Conventionally, a human is shown
Sep 7, 2022
Why it’s Time to Adopt AIOps for Business: Key Takeaways
Artificial intelligence operations (AIOps) and machine learning operations (MLOps) are new subjects and often used interchangeably. AIOps, as defined by
Sep 1, 2022
A Comprehensive Introduction to Uncertainty in Machine Learning
Uncertainty refers to the lack of confidence for each output of a machine learning algorithm. While it’s impossible to create
Aug 2, 2022
Building a Data Pipeline For Scalable AI: Key Takeaways
Learn about the key factors when scaling AI - Data Quality, Expertise, Edge Case Management, Continuous Training, Security and Governance.
Aug 2, 2022
insideBIGDATA’s ‘Heard on the Street’ Features iMerit
Read key takeaways from insideBIGDATA’s article highlighting thought-leadership commentaries from members of the big data ecosystem.
Jul 26, 2022
Data Labeling for Machine Learning
For supervised learning applications such as image recognition, sentiment analysis and time series forecasting, the quality of labeled data dictates
Jul 21, 2022
Data Labeling Services – Why They Matter to Our Future
For decades, science fiction writers have painted pictures of worlds where artificial intelligence (AI) and robots play a crucial role
