Hi There !

I'm Ipsita Mishra

A Final Year Computer Science Student

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About Me

I am Ipsita Mishra, a final year student pursuing BTech at GIET University, Gunupur, Odisha and my major field of Study is Computer Science and Engineering. Currently, Working as a Google DSC Campus Lead. I have a strong proficiency in AIML, Data Science, and Cloud technology. I'm an enthusiast in these fields and have actively engaged in various projects and internships to deepen my expertise.

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Skills

Programming Languages

Python

C

Java

SQL

Frameworks

Tensorflow

Keras

Scikit-learn

Web Development

HTML

CSS

JavaScript

Data Visualization

Matplotlib

Excel

Tableau

Google Sheets

Data Science

Data Analysis

Natural Language Processing

Computer Vision

Core Subjects

DSA

OOPS

DBMS

Statistics

OS

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Education

BTech in CSE

GIET University, Gunupur, Odisha
2021 - 2025

Higher Secondary

Sri Chaitanya Techno School, Visakhapatnam, AP
2019 - 2021

Matriculation

S.V.B.V, Koraput, Odisha
2009 - 2019
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Experience

URSC, ISRO

Data Analyst Intern
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    • Conducted comprehensive analysis of telemetry data to identify patterns and insights, enhancing data-driven decision-making processes.
    • Built and validated predictive models using telemetry data, achieving a 15% improvement in prediction accuracy.
    • Streamlined and optimized data preprocessing pipelines, resulting in a 20% reduction in data processing time.
    • Documentation and Reporting,
    • Continuous Learning.
    • Created detailed reports and documentation on data analysis findings and suggested actionable improvements.

IIT Indore

Data Science Intern
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    • Developed and fine-tuned deep learning models for image and text data, improving system accuracy by 20%.
    • Collaborated with a cross-functional team to implement scalable deep learning solutions, reducing processing time by 25%.
    • Designed and optimized data preprocessing pipelines, enhancing model performance and data integrity by 30%.
    • Conducted research on advanced deep learning techniques, contributing to a project that achieved a 92% accuracy rate in predictive analytics.

Google DSC

Campus Lead
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    • Selected among India's top 700 students as GDSC Lead.
    • Trained by Google in Data Science, ML, and Google Cloud Platform.
    • Addressed students globally as a speaker at over 15 events.
    • Selected as Google Cloud Facilitator, trained and guided 150+ students, with 100% achieving certification.
    • Also selected as Google Gen AI Facilitator, trained and guided 150+ students, with 80% achieving certification.
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Projects

Optical Character Recognition Model

Deep Learning , Computer Vision , Neural Networks

  • Developed a deep learning OCR model using Tensorflow and Keras that recognizes handwritten alphabets.
  • Used a dataset consisting of 28x28 pixel images of handwritten alphabets, with a total of 372,037 entries.
  • Evaluated the OCR model on a test set, achieving a accuracy of 98.16%.
Source Code

Book Recommendation System

Collaborative Filtering , Popularity Based

  • Implemented an item-based collaborative filtering method for the recommendation system and used cosine similarity to calculate item-item similarities and generate accurate recommendations.
  • Developed a Popularity Based Recommender System that handpicked the top 50 books with the highest average ratings, considering only those that received a minimum of 250 ratings.
Source Code

Deepfake Detection

Deep Learning

  • This Projects Aims In Detection Of Video Deepfakes Using Deep Learning Techniques Like ResNext And LSTM.
  • We Have Achived Deepfake Detection By Using Transfer Learning Where The Pretrained ResNext CNN Is Used To Obtain A Feature Vector, Further The LSTM Layer Is Trained Using The Features.
Source Code

Criminal Detection

Python, Open CV

  • This project aims to identify Criminal and Missing People to enhance and upgrade the Criminal distinguishing into a more effective and efficient approach.
  • System Will Detect The Face And Recognize The Criminal.
Source Code

Sentiment Analysis Model

Natural Language Processing , Sentiment Analysis , Machine Learning

  • Trained and developed a Sentiment Analysis model using Machine Learning techniques to analyze the sentiments of tweets about National Education Policy 2020.
  • Used the TextBlob library to label and classify tweets as positive, negative or neutral based on their sentiment.
  • Successfully implemented and tested four supervised learning algorithms including Bernoulli Naive Bayes, XGBoost, Logistic Regression, and Decision Tree to improve the accuracy of the model.
  • Achieved an accuracy of 91.2% with the Decision Tree algorithm, which was the best-performing model in the study.
Source Code

Hey devs!! Feeling lost in the Matrix of code?

PRs, Data chats, or existential dread? I got you.

Contact me

Contact me

Call me

+91 8658838323

E-mail

mishraaipsitaa702@gmail.com

Location

Odisha, India