Apurva Avinash Mirge

Dighi,Pune

Mobile: +919*********/+919*********

Email: adgj9e@r.postjobfree.com

Objective :

Seeking a responsible position in an organisation, which gives me a chance to improve knowledge, enhance my skills and enable me to strive towards the overall development of the organisation.

Educational Qualification :

Standard Institute Board/university Percentage /SGPA 10th

Army Public School

Dighi,Pune

CBSE 90

12th

Army Public School

Dighi,Pune

CBSE 78

BE-COMP Dr D Y Patil School of

Engg,Lohegaon,Pune

SPPU 73.09

Highlights:

• Experience in application development using C, C++, JAVA, Python.

• Experience in application development in Java, Python using Procedural as well Object Oriented manner.

• Proficient in Machine Learning skills for multiple types of applications.

• Experience in handling, analysing different types of data sets.

• Experience in Algorithm designing.

• Experience in writing Web Automation, File system Automation, Process Automation scripts with periodic scheduling and logging activity using Python.

• Proficient in Deep Learning skills for multiple types of applications using Neural Network.

• Sound knowledge of multiple algorithms used for Machine Learning from various libraries in Python.

• Experience in Server side web development using Java, Python, PHP.

• Sound knowledge of operating systems internals.

• Good analytical and problem solving skills.

• Technical Skills :

• Programming Languages :

o Procedural language : C Programming

o Object Oriented Programming : C++ Programming, Python o Virtual Machine based Programming : Java Programming o Scripting language : PHP, JavaScript

• Web Technologies: HTML/HTML5, CSS2/CSS3, XML, JavaScript, JQuery

• Python: Python 3.0

• Python Libraries : Numpy, SciPy, Scikit-Learn, TensorFlow, Pandas, OpenCV

• IDE & Tools: Visual studio Code, eclipse, pycharm

• Web Servers: Apache Tomcat 8.0.22

• Database: PL/SQL, MySQL, MongoDB

• Operating System: Windows, Linux

• JavaScript Libraries: JQuery, Angular JS, Bootstrap

• Testing techniques : Unit testing

• Methodologies: Agile, Waterfall

Technical projects:

Project name : Dynamic Ecommerce web app

Technology: JAVA, JAVASCRIPT, MYSQL, HTML, CSS, AJAX Description:

• In this system when the user will register first time,then his/her data gets stored using mysql .

• For validation purpose we used javascript.

• This application is made for ordering cloths .

• Ajax is also used so that the data on the web app will get preserved when we refresh it.

• We deployed our application using apache webserver. Project Name : Periodic Process Logger with Auto Scheduled Log Report Facility Technology : Python

Description :

• This application us developed in Python.

• This project automate process log activity.

• In this project we create log file with the current time and store information about all Running processes as its name, PID, memory usage, thread count number of child process.

• Our automation script executes periodically depends on the time specified by the user using scheduler of python.

• After periodic execution it sends the log file to the specified email address. Project Name : Naval Mine Detector

Technology : Deep Learning with Neural network using Python Description :

• Mine detection and classification using side scan sonar imagery is a challenging problem.

• As opposed to the majority of techniques, several Neural-network-based methods for the

• detection and classification of mines and mine like objects have been proposed.

• Detection and classification of underwater objects in sonar imagery is a complicated problem, due to various factors such as variations in operating and environmental conditions, presence of spatially varying clutter, variations in target shapes, compositions and orientation.

• By using the concept of Deep learning with Neural network we predict whether object is Mine or not.

Project Name : Titanic Survival Predictor

Technology : Supervised Machine Learning with Logistic Regression using Python Description :

• This application is based on supervised machine learning technique.

• There is one data set which contains information about all passengers from titanic such as its

• name, age, seat number, ticket price, height, floor etc.

• We first clean the data set by removing unnecessary entries and columns.

• We apply Logistic regression technique to train our dataset and predict whether the passenger

• can survive or not depends on its data entries.

Machine Learning & Deep Learning Case Studies :

• Iris Species classification using Decision tree algorithm

• Ball classification using Decision Tree algorithms

• Advertisement predictor using Regression

• Iris Species classification using K Nearest Neighbour algorithm

• Brest Cancer Detection using Random Forest algorithm

• Play predictor application using Linear Regression

• Head Brain size predictor using Linear Regression

• Height Weight prediction using algorithm

• Titanic Survival predictor using Logistic regression algorithm

• Diabetes detector using Linear Regression

• Wine type classifier using K Nearest Neighbour

Technical highlights :

• Knowledge of various python libraries.

• Knowledge of php for server side development.

• Knowledge of Front end development using Bootstrap.

• Knowledge of NoSQL database as MongoDB.

• Knowledge of java concepts.

Personal Information:

• Date of Birth: 09/09/1998

• Father’s Name: Avinash Shivaji Mirge

• Mother’s Name: Aruna Avinash Mirge

• Marital Status: Not married

• Nationality: Indian

The above mentioned information is authentic to the best of my knowledge. Apurva Avinash Mirge

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