I thrive on the exhilaration of discovering hidden insights in data through creative analytical approaches. My mind is wired to constantly hypothesize about trends and relationships to uncover problems that can be solved with data.
Check Out My Resume!I'm Ramya Sri Muthuluri 👩💻, Highly motivated and data-driven aspiring Data Scientist with a passion for uncovering hidden insights from complex datasets. I possess a strong foundation in Python, wielding libraries like Pandas, NumPy, and Matplotlib to effectively clean, analyze, and visualize data. My fascination with machine learning has led me to explore algorithms for tasks like classification and prediction. Additionally, my experience in web development allows me to bridge the gap between data and user-friendly applications. I'm proficient in data manipulation tools like SQL, Power BI, and Excel, allowing me to seamlessly extract, transform, and present data for clear communication. Eager to leverage this diverse skillset to contribute to impactful projects at a leading data science company and propel its growth.
Built a news article summarization system using a machine learning model to condense lengthy articles into informative summaries, saving time and keeping users updated on current events. Achieved [performance metric] on evaluation, showcasing potential for NLP applications.
Built a machine learning model to predict breast cancer patient survival, analyzing patient data for risk assessment. This model has the potential to aid healthcare professionals in personalized treatment plans.
![Sentiment Analysis [Isreal and Palestine Conflict Reddits]](/_next/image?url=%2Fsentiment.webp&w=2048&q=75)
This project utilizes natural language processing techniques to classify Reddit comments.Sentiment analysis is a powerful tool that can be used for a variety of applications. It can help businesses understand their customers better. discussing the Israel-Palestine conflict as positive, negative, or neutral in sentiment
This project tackles identifying unwanted SMS messages, also known as spam. By analyzing text content and message patterns, we can build a system to automatically classify incoming texts as legitimate or spam, helping users avoid phishing attempts and promotional clutter.
Customer churn prediction aims to forecast which customers are at risk of cancelling a subscription or abandoning a service. By analyzing customer data like purchase history, support interactions, and engagement levels, we can develop models to identify these at-risk customers and intervene with targeted retention efforts.
Credit card fraud detection acts like a security shield for your money. It analyzes your spending habits and flags unusual transactions, like a large purchase overseas, to prevent stolen card use.Goal is to Identify fraudulent credit card purchases, protecting both you and the issuing bank.
HR data analytics aims to leverage people data to generate insights that inform strategic workforce planning and talent management decisions. Connected Power BI with Excel to import records.
Uncover hidden patterns in your group chats! This project explores machine learning techniques to analyze WhatsApp conversations, identifying trends, frequent topics, and communication styles. Gain valuable insights into group dynamics and how conversations evolve.
This interactive Power BI dashboard visualizes global Covid-19 data, revealing trends in cases, deaths, and vaccinations. Explore patterns and gain insights to inform future public health strategies.
Discover a collection of machine learning algorithms implemented in Python.
Check it outLearn the basics of data preprocessing techniques for machine learning.
Check it out
