NANIKUMAR THANNIRU

Aspiring AI & Data Science Professional

Ongole, IN.

About

Highly motivated and results-driven Artificial Intelligence and Data Science student with a strong foundation in machine learning, deep learning, and data analysis. Proven ability to develop predictive models, build recommendation systems, and extract actionable insights from complex datasets. Eager to apply technical expertise and problem-solving skills to contribute to innovative projects in a dynamic technology environment.

Education

Pace Institute of Technology & Sciences

Ongole, Andhra Pradesh, India
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B.Tech Artificial Intelligence & Data Science Grade: 8.01 CGPA

Vagdevi Junior College

Narasaraopet, Andhra Pradesh, India
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Intermediate M.P.C (Mathematics, Physics, Chemistry) Grade: 7.40 CGPA

Z.P. High School

Valaparla, Andhra Pradesh, India
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10th Standard General Studies Grade: 8.8 CGPA

Certificates

Programming Fundamentals using Python

Infosys Springboard

AWS Cloud Foundation

AWS Academy

Full Stack Data Science & AI

NareshIT, Hyderabad

Skills

Programming Languages

Python, SQL.

Data Science Libraries & Frameworks

NumPy, Pandas, Scikit-learn, Matplotlib, TensorFlow, Keras, MLOps.

Data Visualization & Business Intelligence Tools

Power BI, MS Excel.

Development Environments & Tools

Jupyter Notebook, Google Colab, PyCharm, CMD, MS Word, PowerPoint.

Machine Learning

Recommendation Systems, Predictive Modeling, Supervised Learning, Unsupervised Learning.

Deep Learning

Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Attention Mechanisms.

Data Analysis

Exploratory Data Analysis (EDA), Data Cleaning, Data Preprocessing, Feature Engineering.

Projects

E-Commerce Transactions Analysis using EDA

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Summary

A comprehensive project focused on analyzing e-commerce transaction data to derive actionable business insights and build intelligent systems for sales optimization.

Action Recognition with Attention-Based Neural Networks from Multi-View Video Data

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Summary

An advanced research project focused on developing a deep learning model for effective action recognition from multi-view video data, utilizing attention mechanisms.

NANIKUMAR THANNIRU