DURGA PRASAD ANNAMDEVULA
BCA Graduate | Machine Learning & Artificial Intelligence And Python Enthusiast | Data Science | AI & ML Aspirant
I am a BCA graduate with a strong interest in Machine Learning, Python, Data Science, and AI/ML. I have hands-on experience developing machine learning projects using Python, Scikit-learn, and Streamlit. And. I have developed the project such as the House price prediction project , customer churn prediction project, Fake news detector for students with a streamlit apps
and the Predicting the eligibility for NSAP Using ML in a IBM cloud.I am passionate about learning new technologies, solving real-world problems with data, and continuously improving my technical skills while contributing to innovative organizations.
Professional Experience
Featured Projects
Customer Churn Prediction Project
The Customer Churn Prediction project is a machine learning-based application developed to predict whether a telecom customer is likely to continue using the company's services or discontinue them (churn). Customer churn is a major challenge for telecom companies because acquiring new customers is often more expensive than retaining existing ones. The project uses Python, Google Colab, and Streamlit, along with data preprocessing, exploratory data analysis (EDA), and a Random Forest Classifier to provide accurate churn predictions.
Fake News Detector For Students
Fake News Detector for students Developed a Machine Learning and Natural Language Processing (NLP) based Fake News Detection System to classify news articles as real or fake using textual content. Implemented text feature extraction using TF-IDF Vectorization and trained a Logistic Regression model for binary classification. The system automatically predicts the authenticity of news articles, demonstrating practical applications of machine learning and text classification techniques.
House Price prediction project
A machine learning project that predicts house prices based on features such as number of bedrooms, bathrooms, living area, and other property details. The model analyzes historical housing data to estimate the expected price of a house accurately.
Core Competencies
Education
Achievements
Completed the Data Science with Python course offered by Cisco Networking Academy. Learned the fundamentals of Python programming for data science, including data collection, data cleaning, data analysis, and data visualization. Gained hands-on experience using Python libraries to manipulate datasets, perform exploratory data analysis (EDA), and derive meaningful insights from data.