Python Developer
Resume:
Luvpreet kaur
New Channasandra, Bengaluru – 560067
Phone no:- 991-***-****
************@*****.***
LinkedIn:- https://www.linkedin.com/in/luvpreet-kaur-38b238166/
GitHub:-https://github.com/luvpreet26
Profile Summary
Experienced Machine Learning Developer with a demonstrated history of working on developing machine learning projects, deploying it on cloud platforms and making them as restful service using flask. Skilled in Python, Machine Learning, Deep Learning, Natural Language Processing, C++, R. Strong information technology professional with a Master of Technology (M.Tech.) focused in Computer science with gold medal.
Education
Aug 2010 – Feb 2014
M.tech (Computer Science) from SBSSTC, Punjab with 80%.(Gold Medalist)
Did dissertation on topic:- Emulation of DdoS Defenses Using Deter TestBed.
Created an environment for experimentation on DETER Testbed with different experimental scenarios including legitimate traffic and attack traffic with defense have been created. The contribution to work is script in python for detection and mitigation of DoS attack.
Worked on Python, Deter- TestBed, Snort- IDS.
June 2006 – June 2010
B.Tech(Computer Science) LLRIET, Punjab with 79.69%. (2nd Topper in 3year)
Experience
June 2018 – till now
Machine Learning Developer
Paskon Information and Management Pvt. Ltd
Projects and Employment Summary
Classifying expense bills into categories using SAP Leonardo.
Conversational UI / Making of Chatbot using Dialogflow/RASA, ML- Engine, SLACK Apps and Worked on categories user queries into particular categories using Deep Learning/ Neural Networks
Extraction of Data from RAIN KING Documents for marketing.
Developed keyword extraction tool in python.
Currently Working on Recruitment Analytics Project
Conducting Technical interviews for team.
Dec 2012 – Dec 2013
Assistant Professor
Global Institute of Management and Emerging Technologies Punjab.
Subject Taught:- Object Oriented Programming, Software Engineering, Design and Analysis Algorithms, Python, Artificial Analysis, Linear Algebra
Aug 2010 – Dec 2012
Lecturer
Shaheed Bhagat Singh State Technical Campus, Punjab
Subject Taught:- Object Oriented Programming, Theory of Computation, Database Management System, Design and Analysis of Algorithms.
Skills
Programming Languages:- Python, R, C/C++.
Python Libraries known:- NumPy, Pandas, Matplotlib, Scikit Learn, Seaborn, Keras, NLTK, Tensorflow, Keras, Pytorch, Json, Flask.
Databases:-POSTGRE-SQL,Excel, SQL
IDE's:- Anaconda ( Jupyter Notebook, Spyder), Pycharm.
REST API's:- GET, POST Call creation in FLASK python Library.
Machine Learning Algorithms known :- Supervised Learning (Linear Regression, Logistic Regression, Random Forest (CART ), Naive Bayes, Support Vector(SVM), K-nearest Neighbor(KNN), Decision Tree), Apriori, Association Rule, Word Embedding (word2vec)
RestFull :- OpenApi (Swagger), Flask Micro-Framework
ChatBot Platforms:- Dialogflow, RASA
Erp Systems:- Odoo, Openbravo
Web development Framework:-Flask
Presentation and Visualization Tool:- Power Point, Microsoft Power BI
Operating Systems:- Windows, Linux, Ubuntu 16
Cloud PlatForms Worked On:- Google Cloud Platform, Amazon AWS Beanstalk, AWS Lambda
Non-technical:- Communication, Presentations, Public speaking.
Assignments in Machine learning, Deep learning and Natural Language Processing
Predicting survival of passengers on TITANIC DATASET using SKLEARN
Predicting on which project, activity and how many hour person will work based on his previous history using SKLEARN (RANDOM FOREST)
Resume Summary generation using NLTK
Predicting Handwritten digits using MNIST Dataset using KERAS
Sentiment Analysis using Natural Language Processing using NLTK
Text Classification on 20FETCHNEWSGROUP using SKLEARN, CNN, RNN
Predicting image given is of cat or dog using keras
Learning Projects:-
Resume Parser using Natural Language Processing ( Available on Gitub)
Text Classification using Deep Learning
WorkShop and Courses
Short – Term Course on Data Science From Sgraph Infotech Pvt. Ltd, Bengaluru from March 2018 – May 2018
During Training Learned:-
Python – Interpreted Programming Language.
Statistics and Linear Algebra.
Data Mining and Feature Selection
Machine Learning Algorithms (Supervised and Unsupervised Learning)
Natural Language Processing
Deep Learning
SAP LEONARDO MACHINE LEARNING FOUNDATION course cleared with 63.3%
Attended Google Cloud OnBoard on March 28, 2019
Research Papers
Emulation of Snort on Deter Testbed in ijarcs.
Installation of Intrusion Detection System Snort on DETER TestBed in International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, No. 6, June 2013.
Awards:- Spot Award for Recruitment Analytics Project.
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