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Laxmi Narayana Chilakala

@laxminarayanachilakala

Data Science Enthusiast

Hyderabad

Hitachi VantaraCoursera

Laxmi Narayana Chilakala is a Data Science Enthusiast with 4 years of experience driving technical and analytical projects. He has worked extensively with various Machine Learning models, including Linear Regression, Logistic Regression, Decision Trees, SVM, KNN, Boosting, and Bagging techniques using Python. His expertise covers the entire data science process, from EDA and feature engineering to building and evaluating deep learning models using TensorFlow and Azure ML Studio.

Experience

Data Scientist

Hitachi Vantara

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Worked on Churn AI project to identify customers at risk of stopping purchases. Responsibilities included data analysis, pre-processing, checking collinearity, feature engineering, hyperparameter tuning using hyperopt, and building/evaluating ML models.

Implementation Engineer

Aviso

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Onboarding new clients using existing tools, responsible for creating and maintaining demo data, and providing feedback to continually improve tools and processes.

Data Scientist

Infosys

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Involved in ML Project (CMB) to identify customers eligible for a credit limit increase, covering data analysis, feature engineering, visualization, model building (Logistic regression, SVM, KNN, Decision trees, Random Forest, XGboost, ANN using TensorFlow), hyperparameter tuning, and model evaluation. Also handled DevOps Project (Iceberg/CDE), from initial coding to final deployment, integrating tools with Jenkins CI/CD pipeline, production deployment using Blue-Green Methodology, and monitoring with AppDynamics.

Education

Coursera

Specialization

Deep Learning

Deep Learning Specialization

INSOFE

PGP – Data Science

Data Science

Amrita University

B-Tech

Mechanical Engineering

Skills

Python Programming
Machine Learning
Predictive Modelling
Exploratory Data Analysis
Numpy
pandas
Tableau
Seaborn
Matplotlib
Deep Learning
ANN
CNN
Transfer Learning
SQL
Spark
TensorFlow
Azure DataBricks
Azure ML Studio
Feature Engineering
Hyperparameter Tuning
Problem Solving