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.

Dec 27, 2022

Role of Automation in ML DataOps

Automation in machine learning will enable people to make a bigger impact and have more fulfilling roles.

Dec 13, 2022

Convergence of ML Ops and Data Pipelines

Find out how these leading companies deploy robust ML systems in production by converging ML Ops and Data Pipelines.

Dec 7, 2022

Overcoming the Obstacles of Achieving High-Quality Data

Find out how comprehensive data annotation tools can help overcome the six most common barriers for high-quality data.

Dec 1, 2022

The Stakes Are High: Best Practices For Deploying Responsible AI

Responsible AI is a key investment to help AI adoption and instill trust in end-users.

Nov 24, 2022

Pushing the Frontiers in AI For Billions Around the World

iMerit CEO Radha Basu and Meta’s Manohar Paluri discuss the ideal framework for pushing the frontiers in AI research at the ML DataOps Summit.

Nov 11, 2022

Automated Document Classification Using Machine Learning

Here’s how machine learning can help categorize text-based documents using supervised classification algorithms.

Nov 7, 2022

Four Defenses Against Adversarial Attacks

Learn how and why DNNs are vulnerable to adversarial attacks, and how to make machine learning models less vulnerable to these attacks.

Oct 27, 2022

Using Neural Networks for Video Classification

As videos have become easier to distribute and consume, we have seen considerable developments in machine learning algorithms that can

Oct 20, 2022

Classifying Images with Artificial Intelligence

Learn about the basics of image classification with this tutorial on convolutional neural networks with Tensorflow. A sample script is included.

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.