Laxman Madasu
A Data Scientist with a BS in Data Science, specializing in Python, ML libraries (NumPy, Pandas, NLTK), and MySQL. They build intelligent, AI-powered ...
About
A Data Scientist with a BS in Data Science, specializing in Python, ML libraries (NumPy, Pandas, NLTK), and MySQL. They build intelligent, AI-powered applications, demonstrated by projects like an MCQ Generator (Streamlit, Gemini) and a Code Reviewer (Python, Streamlit, OpenAI API). Their expertise lies in transforming data into practical, innovative solutions, leveraging cutting-edge LLMs to solve real-world problems efficiently.
Skills
Programming Languages
Python
Data Science & ML Libraries
NumPy
Pandas
Matplotlib
Seaborn
NLTK
Scikit-learn (Sklearn)
OpenCV
TensorFlow
Machine Learning Concepts
Supervised Learning
Unsupervised Learning
Feature Engineering
Data Preprocessing
Hyperparameter Tuning
Model Deployment
Artificial Neural Networks (ANNs)
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs)
Data Augmentation
Regularization Techniques
Bag-of-Words (BoW)
TF-IDF
Transfer Learning
Generative AI & NLP
Large Language Models (LLMs)
Transformers
Attention Mechanism
Hugging Face
LangChain
OpenAI
Google GenAI
Gemini Model
Web Frameworks/Tools
Streamlit
Statistical Analysis
Descriptive Statistics
Inferential Statistics
Probability
Hypothesis Testing
Database Management
Joins
Stored Procedures
Triggers
Views
Indexes
Projects
MCQ Generator Web Application
Streamlit
Gemini model
Developed an MCQ Generator Web Application leveraging Streamlit for an intuitive UI and the Gemini model for instant, high-quality question generation. This tool empowers users to transform any text into customizable multiple-choice questions (5, 10, 15, or 20), streamlining content assessment and learning material creation. It provides an efficient solution for educators and trainers to rapidly produce engaging MCQs.
Code Reviewer and Bug Fixing Tool
Python
Streamlit
OpenAI API
Developed a Python application using Streamlit and OpenAI API to review code and provide feedback on bugs and fixes. Created a simple interface where users can submit their code and get instant feedback. Implemented an efficient system to analyze code, detect bugs, and suggest accurate fixes using the OpenAI API. Made the tool easy to use, helping developers improve their code quickly.
Dog Breed Prediction
Convolutional Neural Network (CNN)
Streamlit
Data Augmentation
Transfer Learning
Engineered a Convolutional Neural Network (CNN) model to accurately predict dog breeds from images using a comprehensive dataset. Created an interactive Streamlit application that allows users to upload dog images and receive real-time breed predictions. Implemented functionality to visualize and display extracted features from the CNN at every convolutional layer, enhancing model interpretability. Optimized model performance through techniques such as data augmentation and transfer learning.
Sentiment Analysis of Hotel Reviews
Machine Learning
BoW
TF-IDF
Naive Bayes
Logistic Regression
XGboost
Streamlit
GitHub
Evaluated hotel reviews for sentiment classification using machine learning techniques. Preprocessed text data and extracted features with BoW, and TF-IDF. Trained and evaluated models: Naive Bayes, Logistic Regression, and XGboost. Developed and deployed a real-time sentiment analysis app with streamlit. Achieved 83% accuracy in sentiment classification and documented the project on GitHub.
Education
Bachelor's of Science, Data Science
Nsv Degree College
01/01/2020 - 31/12/2023
Certifications
Certificate of Course Completion in Data Science
Innomatics Research Labs
Module Completion Certificate on Exploratory Data Analysis
Innomatics Research Labs
Machine Learning with Python
IBM Developer skills Network