Currently a graduate from University of Texas Arlington in Computer Science & Engineering. Anirudh has a very good problem solving ability - mathematics and algorithms. Passionate and determined to taken on hard and difficult problems. I have worked on various areas of computer science ranging from software development to artificial intelligence and machine learning. I have an industry experience in Wipro Technologies Bengaluru. The project was on The Internet of Things Domain. My role was of a Software Engineer intern. During my term as an intern, I was fixing bugs in the UI for their software that is the front end. I used Javascript and PHP. Additionally, I have an interest for machine learning and data analytics. I have taken courses on AWS on LinkedIn and udemy, I also have an interest towards cloud computing and big data technologies.
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Experience
Software Engineer intern
Wipro Limited
Name of Product: Connected cars Domain: Internet of Things
Fixed bugs and developed additional features based on client
requirements. Did functional testing for 75 mobile
applications. Did performance, stress testing and load testing on the
application to determine the total number of concurrent and
normal entry of users in the application using JMeter &
BlazeMeter. Did a successful test on the application and submitted a report
after the test.
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Projects
1. Project on building a social networking site mSangeet
Social networking website to allow all age groups to attend
traditional & classical music performances by famous singers.
Implemented maps for locations & granted facebook access for children under the age of 18.
I took care of some of the front end side like designing the singer's profile using CSS3, HTML5 and Bootstrap. Back end side like sending
emails to the respective singers and much more. Used technologies like PHP, CSS3, Javascript, Javascript framework
stack like AngularJs, NodeJs, ExpressJs and Mongo db(MEAN.js)
2. Generation of Electronic Health Record (EHR) and
Platform for doctors, patients and hospital. Developed the doctor, patient and the hospital modules. Loaded the Dataset of 1 lakh patients to a Mongo DB database. Generated the electronic health record by getting details from
patient like symptoms for the disease. Technologies used are Mongodb for data base and Java for front end
and backend, Maven for build.
3. Graduate Admissions Predictor (08/2019 – 01/2020)
Loaded dataset and performed data cleaning, formatting and data normalization using Z-score metric. Grouped similar type of colleges using groupby & determined the
rejection and acceptance rate for the respective colleges through pie
chart, vertical bar graph, horizontal bar graph and line graph. Visualized the dataset in Tableau and found out a story which tells us GPA was the metric for acceptance or rejection of applications. Performed K-Means Clustering for grouping similar data & KNN
algorithm to predict Admit or Reject using sklearn. Divided the dataset into training and test data set in the ratio 80:20 %
4. Heart attack prediction of patients using ML
(05/2019 – 06/2019)
Learning the features from the dataset and excluding unnecessary
features. Normalizing and doing data cleaning on the current data. Then Performing K nearest neighbors to classify the dataset if the person has heart disease or not.
Implemented PCA algorithm to do feature learning and reduced the number of features by 16% (from 13 features to 11 features) then
implemented KNN to classify from the dataset if the person has heart
disease or not based on the given test data.