Learning about Microsoft Cognitive Services
At Cloudreach we have core values such as “Be One Step Ahead” and “Promote Personal Growth”. They help us to ensure that we are always up to date with the latest trends of the rapidly evolving public cloud, as well as exploring new technologies.
With the help of our Growth & Development team we are encouraged to leverage benefits of online courses as well as both internal and external training. As we work with cutting-edge technologies, our partners also help us to maintain the highest level of expertise and keep us up to date with the latest trends they deliver on the market.
Over the last few months we have enjoyed the Microsoft Cloud Solutions Architect team presenting the latest Azure trends during our Friday’s educational sessions or “Tekkie Teas”.
With the help of our Microsoft Partnership team, it was proposed to organise a day of hands-on training around Microsoft Cognitive Services: Machine Learning (ML), Vision API, ChatBot and others.
The training was led by Mahesh Balija, a Big Data veteran passionate about ML, Deep Learning, AI and Quantum Computing, as well as building relationships with partners and helping them on their Digital Transformation journey. He was the perfect candidate to deep dive us into these progressive technologies.
Training was filled with presentations around Cognitive Services, discussions around practical use cases, existing case studies as well as demonstrations and practical hands-on labs.
It is possible to get yourself familiar with the training materials on your own. They are fully available, for free, on GitHub.
To proceed with the labs – you will need to do an initial setup of the tools and services described in the setup section of the AI Bootcamp. All steps are well described and straight forward, so don’t worry if you are just beginning your journey with Azure.
In some of the sections of the lab (like Image Processor) you may find that it looks like you need some C# knowledge to proceed. Don’t be afraid, just read the whole page – you will find detailed explanations or shortcuts for dummies :). It’s only used as the code for the desktop applications that you’ll use to evaluate Cognitive Services within the lab.
Value Added Services
A good example of the great value added services would be “Custom Vision API”. This service offers an easy and reliable way to create your own custom ML models to process different pictures. It could be used in a variety of business domains that receive pictures as input from the customers. The use case we covered in the lab was related to an insurance company processing photos of vehicles that either need repair or should be considered as a loss, but it could be used in a variety of other organisations to increase the speed of processing and reduce amount of the manual work, which would of course reduce the operational costs.
The other great example of AI that we have covered during the workshop was ChatBots. They can easily be customised and integrated within the organisation for the interaction with internal and external users as well as for entertainment purposes.
QnA Maker is an easy-to-use web-based service to train AI to respond to user’s questions in a more natural, conversational way. Thanks to a question and answer service with a graphical user interface, you don’t need to be a language expert to train, manage, and use it widely.
If you have a web based knowledge base (FAQ) – it will take just few moments to configure and try.
Taking all the best aspects from the training, we can now be sure that we will be able to help our customers to address their existing challenges in the cloud journey with cloud-native ML and AI services.
If you are interested in understanding how such services can be used within your organisation and want to run a demonstration or proof of concept – feel free to reach out to us, as we now have a team of trained individuals that would be happy to assist.
Keep it Cloudy!