adm2wo@r.postjobfree.com 996-***-****

Bengaluru, India 30 June, 1999

linkedin.com/in/rachana-s-iyengar-3021461ab github.com/Rachana-1999 Jupyter Notebook R Studio Tableau MySQL

Rachana S Iyengar

Excelled in data science and machine learning course work. I have aspirations and a great zeal to work as Data Scientist and passion for gaining practical knowledge.

EDUCATION

10th Standard

Sri Aurbindo Vidya Mandir

07/2013 - 04/2014, 78.88%

2nd PU

KLE Independent PU college

06/2015 - 04/2016, 74.66%

BE

Sambhram Institute of Technology

08/2016 - 08/2020, 6.28

PROJECTS

Loan Status Prediction

Tools and Techniques - Python, Feature Engineering, EDA, Plots, scikit-learn, numpy, pandas, Logistic Regression.

Business Objective - predict the customers who are more likely to default on loan and find the key predictors which have major impact on default.

Recommendation System

Tools and Techniques - Python, Feature Engineering, EDA,scikit-learn, numpy, pandas.

Objective - to predict the user's wish list and to supply them with the best list of recommendations. The business end goal is usually to increase sales, revenues, user engagement. Credit Card Fraud Detection

Tools and Techniques - numpy, pandas, seaborn, matplotlib, Random forest

Business Objective - The key objective of any credit card fraud detection system is to identify suspicious events and report them to an analyst while letting normal transactions be automatically processed.

Breast Cancer Detection

Tools and Techniques - numpy, pandas, matplotlib, seaborn, XGBM

Business Objective - To make a decision by analyzing patient reports, Early diagnosis of any disease can be curable with a little amount of human effort.

DATA SCIENCE COURSE

EDA : Analysis on the overall data identifying outliers, correlation, treating missing values.

Text Mining : Built models using Bag of words algorithm and obtain word clouds.

Ensemble Learning : Knowledge on Stacking, Boosting, Bagging.

Model Building : Regression, Decision Trees, Random Forest etc.

Deployemnt : Deploying ML model in Streamlit

SKILLS

STUDENT ORGANISATION

Engineer Without Borders (EWB) (2018 - 2020)

CERTIFICATIONS

Data Science

ExcelR Solutions

Internship Project

Innodatactics

Text Analytics 101 (TA0105EN, provided by cognitive class) IBM Developer Skills Network

Data Science using machine learning with python and R IBM Developer Skills Network

TOOLS

Google Colab

Microsoft Word Microsoft PowerPoint

Tools - Jupyter Notebook, R studio, Tableau, Microsoft Excel, Microsoft Word, Microsoft PowerPoint

Python Libraries - Pandas,Numpy,Sckit-Learn,NLTK and many more

Data Visualization - Tableau, Seaborn, Matplotlib

SQL - Performing Basic Queries.

Deep Learning – Neural Networks.

Natural Language Processing – Text Processing, Sentiment Analysis.

Programming Languages - Python, R (Basics)

Machine Learning Algorithms for regression – (Linear / Multi Linear / Logistic), Classification( Decision Tree / Random Forest / SVM / KNN / Naïve

Bayes),Clustering(Hierarchical, K- means).

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