Improve AI/ML Model Outcomes with Data Annotation Services - PowerPoint PPT Presentation

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Improve AI/ML Model Outcomes with Data Annotation Services

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Before beginning with data annotation in machine learning, just imagine—how would a computer vision-based model detect a face in the photo? The only way for a smart model to detect a face in the photo is because of the other photos already existing labeled as a face. Get in Touch: #dataannotationservices #dataannotationinmachinelearning #dataannotationcompanies #damcosolutions – PowerPoint PPT presentation

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Title: Improve AI/ML Model Outcomes with Data Annotation Services


1
Improve AI/ML Model Outcomes with
  • Data Annotation Services

2
Table Of Content
  • Introduction
  • Data Annotation in Machine Learning Techniques
  • Semantic Segmentation
  • Bounding Box
  • Named Entity Recognition
  • Conclusion

3
Introduction
Training an AI/ML model requires supervised
trainingit is done by leveraging the strategic
combination of the human-in-loop and the latest
technology. The annotators leverage certain
techniques for machine learning data annotation,
some of which are mentioned here.
4
OUR COMPANY
  • Being a seasoned data annotation services
    company, Damco holds expertise in catering to
    different industries and assisting them with data
    labeling for machine learning.

5
Data Annotation in Machine Learning Techniques
  1. Semantic Segmentation
  2. Bounding Box
  3. Named Entity Recognition

6
Semantic Segmentation
Semantic segmentation is also known as class
segmentation, as it helps in differentiating
between different classes of objects. It is great
for grouping objects as it assigns the same label
to each member of the object class. Apart from
this, it helps in understanding the presence and
location of objects.
7
Bounding Box
The bounding box is one of the most basic types
of data annotation techniques. In this method,
rectangles and squares are drawn around the
object of interest so that it can be recognized
easily. It is most helpful when the objects are
relatively symmetrical or when the shape of the
object isnt important.
8
Named Entity Recognition
In this technique, words in the text are labeled
with pre-defined categories like name, place,
date, etc. As AI learns the keywords, machine
learning models also easily understand the topic
of the text all thanks to the Named Entity
Recognition (NER) method.
9
Conclusion
Any AI model is as smart as the data it is fed
therefore, ensuring that the data sets are
accurately labeled is a must. Errors or
inaccuracies in the data labeling process deviate
from the outcomes, and harm your business rather
than supplementing it. Growth-focused leaders,
therefore, resort to data annotation services.
10
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
11
Thank You
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