Annotation in Machine Learning – The Key to Fueling Smart Models

1
Annotation in Machine Learning The Key to
Fueling Smart Models
2
Table of Content

• Introduction
• Why Professional Data Annotation Services?
• Professional Excellence
• Technological Competence
• Data Integrity
• Industry Compliant Practices
• Comprehensive Suite of Offerings
• Conclusion

3
We offer customized data annotation services to
a wide network of B2B and B2C clients. Having
in-depth experience, our annotators develop
enhanced training sets to be fed into machine
learning algorithms
4
Introduction
Supervised traininga strategic combination of
human expertise and the latest toolsis required
for an AI/ML model to act and make decisions,
highlighting the need for data annotation in
machine learning.
5
Why Professional Data Annotation Services?

1. Professional Excellence
2. Technological Competence
3. Data Integrity
4. Industry Compliant Practices
5. Comprehensive Suite of Offerings

6
Professional Excellence
The accredited annotators have proper
model-behavior understanding and develop training
sets according to their future use case, thereby
helping the AI/ML models easily identify the
objects.
7
Technological Competence
The professionals can efficiently process huge
qualities of raw data, remove biases and errors
thus creating a constant stream of structured
data sets.
8
Data Integrity
The professional providers follow stringent data
security protocols. Having multi-layer security
check systems in place ensures that the data
integrity remains intact.
9
Industry-Compliant Practices
Companies dealing with data must strictly adhere
to various data-related laws including HIPAA,
GDPR, PII, etc. The outsourcing data annotation
companies stay updated with all such rules and
regulations. All their practices are legally
compliant and abide by the set-industry standards.
10
Comprehensive Suite of Offerings
The external providers provide a comprehensive
suite of offerings including text annotation,
video annotation, image annotation, audio
annotation, etc everything under one roof.
11
Conclusion
In a nutshell, annotation in machine learning is
important to help AI-based models grow. Engaging
in professional services enables the stakeholders
to get constant access to voluminous streams of
training sets without compromising on the quality
of data.
12
Contact Us
2 Research Way, Princeton, New Jersey 08540,
USA  1 609 632 0350  info_at_damcogroup.com https
//www.damcogroup.com/data-support-for-ai-ml
13
Thanks
Thanks
Please keep this slide for attribution.