Basic Principles of Human-in-the-Loop Machine Learning

Introduction: Human-in-the-Loop (HITL)

Human-in-the-loop or HITL is defined as a model that requires human interaction. Basically, Human-in-the-loop is the branch of artificial intelligence that combines both human and machine intelligence to create machine learning models. 

The HITL approach combines the best of human intelligence with the best of machine intelligence. Machines can make smart decisions from large datasets, while people are much better at making decisions with very less information. Humans also provide labeled data for model training and that’s one of the most important tasks in the AI system. To power Machine learning we use Advance Data labeling Techniques that improve the quality of training data in an interactive manner after human correction takes Less time and greater output. Nothing is more essential than quality data in Machine Learning 

Human in the loop is used in many use cases covering NLP, computer vision, sentiment analysis, transcription etc. 

Humans + Machines = Trained Machine Learning Algorithms

Basic Principles of Human-in-the-Loop Machine Learning

  • Maintaining quality 

One of the most basic principle is to maintain multiple quality control methods to match or exceed quality standards to meet our client’s expectations and AI system requirements.  Poor quality training data for your machine learning model can be terrible and will surely lead to wrong predictions and conclusions. 

  • Experienced data Annotators

Most important principle to cover under Human-in-the-loop machine learning is to have well experienced data annotators to run the AI project in a perfect manner. As efficient and effective Professionals,  trained teams & Experienced data annotators will make the human in the loop machine learning easier & faster. Well trained annotators for every project provides High-quality, and accurate data with less turnaround time. 

Scalability & Flexibility 

A necessary principle is the Ability to deliver data annotation and data labeling at scale. Working with hundreds of workforce to annotate as per the demand and providing a completely scalable solution to meet different clients’ needs.

YOUR DATA OUR RESPONSIBILITY 

Learning spiral, Data Labeling company has a workforce with a diverse set of skills and the ability to deliver data annotation and data labeling at scale. Learning Spiral enables businesses and organizations to get work done easily and quickly when they need it.  Our affordable annotation services provided by trained in-house dedicated professionals will ensure customized annotation services and high quality labeled data to meet your needs.

Leave a Reply

Your email address will not be published. Required fields are marked *