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.
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
Issued By
Infosys Springboard
AWS Cloud Foundation
Issued By
AWS Academy
Full Stack Data Science & AI
Issued By
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
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.