Tricks and Guideline to Deploy AI in IoT (try) ( FREE )


Mathematical Theory

Data Set

AI Model Design

Training AI Model

Save AI Model

Load AI Model

Micro Inference Service

Deploy in Edge

Case Study 1: J7 App

Case Study 2: Kanshi

Case Study 3: IoT in 5G

Case Study 4: Healthcare

Case Study 5: Agriculture

Visual Recognition : IBM Watson

Silicon Vendor to Edge device

Recommended infra Architecture


Niranjan Kumar had designed and implemented Back propagation algorithm island and other required code to train NN / CNN Deep Learning Models. Above mentioned contributions had come during his higher secondary school days. Presently, Niranjan Kumar is a 3rd year student of B.Sc. (Honours) Mathematics and Computer Science, Chennai Mathematical Institute. ( ) . Before joining CMI, Niranjan Kumar had worked extensively in Back Propagation Algorithm and its use in Optimization

Niranjan Kumar

Student - B.Sc. Mathematics

niranjan at cmi dot ac dot in

Jayakumar. S had worked on Dltrain platform by using contributions from Niranjan Kumar. DLtrain is used to train students in large scale by online and also as a tutorial session n IEEE conference during 2019. DLtrain is used to train faculties ( vai Faculty Development programs in many colleges and universittes ) in AI and deployment of AI in Edges.

Jayakumar S PhD IIT Mumbai

Baranovichi State University had used DLtrain to train their teaching staff and research students such that they can use it in AI projects. Same is given in details and also the same is used by many other students across the Global to learn deployment of AI applications in IoT edges.