Do we really need data scientists to create a solution using
machine learning?
Well, previously, yes. It’s a must.
But now thanks to Azure
cognitive services, those can be done by a developer.
If a developer wants to
take the advantage of AI and features cognitive service provides which is
vision, speech, search, text processing, language understanding this will be
the best way.
Anyone who can write a simple program, means who writes basic
code can use this feature and create AI models using AML. But the problem is
scaling. Most of the time model developers facing this problem and now there
is a solution for that too. Container Support for Cognitive Service. It is much
easier to use and just build and deploy.
This allows developers to build big AI systems that run at
scale, reliably, and consistently in a way that supports better data governance.
Ex: A School System
First things first. There may be some entities for main actors
for teachers and children. But later on there will be many other entities will
be there such as, attendants, notes, news etc. So while its grow its hard to
maintain and scale it once it’s on production.
For this, can use these kind of solutions (Cognitive Service) to
keep track and scale easily.
When it comes to large scale apps, it’s so much easy to maintain
the app as well.
There are 4 key
capabilities within Azure Cognitive Services
1. Text Analytics Container
- Key Phrase Extraction
It creates a key word by searching words and
return those key word by using AI.
Ex:
“what are the nearby coffee shops to go?” (Coffee shop, nearby)
- Languages
Supports up to 120 languages
- Sentiment Analysis
This work as raw text analysis and returns a
value in between 0 and 1 where 1 is the most positive
2. Face Container
Face detection is a most valuable fact now days which each and
every device has the feature. So the API detect the face, verify and most of
the time it is trained to detect emotions even. It is a common framework runs
underlying and user can easily set up security, storage and logging for his
container.
3. Recognize Text Container
OCR (Optical character recognition) has improved in here and
this can detect text from 120 languages and of various objects and backgrounds.
4. Custom Vision Service support for logo detection
Custom Vision Service will add support for logo detection,
allowing business to create their own logo detector quickly and easily. Logo
detection is a specialized type of object detection suited specifically for
logos that can be small, skewed, or obfuscated within a larger picture, for
example on the sidelines of a soccer match, on a building sign in a cityscape,
or on a scanned form. Now you can build your own logo detectors to help search
and locate their logos in their media libraries or to generate analytics for
their social media feeds.
While supporting to each and every thing, why not object logos? Users can create their own logo detectors which to identify their businesses.
It is a bit advanced algorithm and it will detect specially logos and brands.
Those logos might be blurred, small, fuzzed, no matter what it will detect it.
Read full article on Azure Blog:
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