Internships

Ismile Technologies

I was a part of the Enterprise Data Science team which was developing products around Artificial Intelligence/ Machine Learning domain. I was a part of two teams – Ecommerce Bots and Hospital IOT.

Health Care and Life Sciences

I am a team lead for Hospital IOT product, this is a project under Health Care and Life Science domain. There is no doubt that this industry needs a whole lot of attention than it gets. We are planning to automate and reduce the resources associated with the patients. Every patient needs the attention of at least on nurse/one caretaker. To eliminate this person, we are trying to automate the system using two models: Facial Expression Recognition and IOT devices model

IOT devices Model:

We are planning to take the vital values from the IOT devices connected to the patient in real time. Develop a ML model over it. Using anomaly/ outlier detection we will find the unstable or not normal state of the patient to the doctor. We will be using Microsoft Azure as our cloud component due to its rich support to the Health domain. For the notification part, we will be notifying using two components, one is Power BI- we will create visualization of the vitals so that the doctors and other backend people can understand the cause of the unstable behavior of the patient, second is the application notification- mobile application to notify the doctor about the instability.

Facial Expression Recognition:

For this part, we have leveraged the readily available code. This module is developed using keras and has the ‘pain’ attribute in it. With pain it also detects these emotions: anger, disgust, fear, happiness, neutral, sad and surprise. But as the matter of fact, we are interested in ‘pain’. The camera will be setup to detect the patient expressions, which will be modeled over the cloud. Whenever out model outputs pain as the expression, we will notify the allocated person saying that the patient is in pain and needs immediate attention.

E-commerce Bots

Bots are the future of engagement between the user and brand or let us just say, the fan and the celebrity!! We are planning to develop a chatbot for client ecommerce website using AWS Lex. We will chat with the user and try and find attributes like their age, gender and if they are interested in the respective product etc. Using these attributes to the apriori algorithm, we will get the products that are most suitable for the user. This will be done using the support and confidence from the algorithm. The bot will then offer these products to the user and help them direct to the website of the respective product. This will increase the engagement of the user with the website.

DigitalNil

Performed visualization of website’s visitor’s data using apache Hadoop tools

• Liaised with a team of ten to draw conclusions from web logs generated by clickstream data
• Analysed and selected appropriate web logs from Adobe Omniture and uploaded to HDFS by Apache Ambari
• Parallelization, dataset analysis and abstraction map reduce was done by Apache Pig
• Data Selection process was done by eliminationg non usable fields and views were created on the tuples
• Partnered with team members and visualized queries using maps, bar and Y charts after ODBC connections
• Evaluated average age, popular states/country, popular gender, average visits of URL, by execution of project

Zensar Technologies

ESD Program

• Zensar Technologies is an IT services and infrastructure services provider.
• This program included three modules Frontend, Backend and Soft Skills. We were trained by Sr. Corporate Trainer Manish Sharma
• We learnt a lot about Java, Json, SQL, MongoDB during this training.
• The Soft Skills part was taught by Mr. Tanveer Ahmed were we learnt a lot about team building, confidence and presence of mind