(M) 099**-***-*** firstname.lastname@example.org
Bangalore - 560075
● Programming languages: Python, SQL, C++
● Machine learning
● Microcontroller programming
● MATLAB - logging in sensor data to analyse power quality. Experience and education:
Internship (6 months) Flutura Decision Sciences and Analytics PG Diploma Data Science IIIT-B on going
BE EEE [2013-2017] Coimbatore Institute of Technology, Autonomous under Anna University
Mount Carmel College, Karnataka P.U. Board
S.S.L.C. Poorna Prajna Education Centre,
Karnataka State Secondary Education
● Multiple exploratory data analysis and detecting operational anomalies in the wind turbine and mechanical engine data sets
● Used statistical methods and machine learning models (decision trees, random forests, isolation forests and svm).
● Industrial trainee - Salzer Electronics (November 2016-December 2016)
● Udemy :Machine learning A-Z
● Udemy :Deep learning A-Z
● Coursera : Andrew NG Machine learning
● Attended a workshop on PLC from College of Engineering, Anna University, Guindy
● Completed a course on Embedded system design using ARM and Texas Instruments MSP430 micro-controller family conducted by LI2 Innovations.
● introduction to the motivation behind gaussian mixture models and neural networks . complex data sets being learnt with tensorflow and implementation of image recognition with convolutions, text processing with NLP.
● HOUSE PRICE PREDICTION USING PUBLIC DATASET
Performed price dynamics analysis
Implemented prediction model with advanced regression method Used public data set for verification
● SOLAR POWERED MULTIPURPOSE AGRICULTURAL ROBOT
The robot was powered with a solar-battery combination and controlled using an Arduino and a driver circuit.
Performed functions of obstacle detection, locomotion, drilling and seeding and monitoring the soil moisture at a timed interval and specified distance. BLE integration for communication. Continuous monitoring of the moisture content of the soil was ensured. Simulation performed in MATLAB.
● DESIGN OF A VIENNA RECTIFIER FOR A STAND ALONE WECS The Wind Energy Conversion System (Standalone) was provided with an alternative converter to the conventional diode bridge rectifier. The Converter was simulated using PSIM software and a prototype model was designed. The Vienna rectifier showed improved output performance. Methods to improve the feedback and the output gain of the system and to make it operate at variable input was explored. Overall roles I have played:
As an intern the following tasks were done using python :
● Cleaned the datasets depending on the objective .
● Prepared the data sets according to the unsupervised models that had to be implemented.
● Performed exploratory data analysis using statistics and machine learning.
● Required outlier treatment and feature engineering was done.
● Visualization of various sensor data.
● Implementing models and finding anomalies and the factors that led to the breakdown or malfunction of a particular unit.
Date of Birth 12th October 1994
Languages Known English, Hindi, Kannada, Malayalam, Tamil, Elementary German