DANUSHMATHI P

Passionate Data Scientist with a knack for turning complex data into meaningful insights, skilled in using statistical analysis and machine learning to solve real-world problems and support better decision-making. Strong expertise in Python, with a focus on collaborating with teams to create innovative solutions that enhance efficiency and drive success. Committed to continuous learning and always eager to apply new analytical techniques to support data-driven initiatives.

• AWS -Cloud 101
• Google developers - Python and Deep Learning
• Programming Hub Google developers -Python
• NVIDIA -AI & Deep learning
• Kaggle -Python
• Shape AI -Python and Deep learning
• Cousera AWS - Python with Machine learning
• Perfect plan B - Google colab Machine Learning

• High School English Rotary Club president
• College Special Lab Represntative
• 1 ST PRIZE - Won Mr.Poet title in National level poetry writing
• 2ND PRIZE -Won in poetry writing in World Tamil Day contest
• 2ND PRIZE - Won in Adzapp Spotlight'20 Content creating contest
• 3RD PRIZE -Won in Drawing in World Tamil Day contest
• 3RD PRIZE- Won in DeXigner Doodle design thinking contest in National Engineer's Day

• Creativity-Poetry writer,Doodle artist
• Collaboration and Teamwork
• Decision maker and problem-solver
• Effective Communicator
• Freelancer in article content writing

1. BID.IT-Bidding and E-Auction Website for Farmers

• https://shorturl.at/sL8wi

2. Generative AI-Tech ChatGPT

• https://shorturl.at/Bu5hm

The Patent Act, 1970 under Government of India

• Grocery Distribution using Cloud Medical(Application Number:202241029667)
• Medical E-Prescription (Application Number:202341000535)

CONTRIBUTION

• Team leader
• Full Stack developer
• Web-Hosting
• Data Analytics
• Software tools support

• Technologies used : HTML, CSS, JavaScript, Bootstrap, PHP, API, CI/CD Pipeline, Mergo, Razorpay, Analytics, AWS Big Data, Cloudflare and Ec2.
• An online auction and bidding platform with automatic future price prediction using a Genetic algorithm.

• Technologies used: Advanced analytical methods, such as clustering or time series analysis , are employed to identify segments of riders or predict demand patterns.
• Exploratory data analysis techniques are applied to uncover patterns, correlations, and anomalies within the dataset.

• Technologies used: Machine learning models such as regression, clustering, and recommendation systems , are trained on the processed data to make accurate predictions also uncover hidden trends.
• The analysis encompasses areas such as customer segmentation and inventory management, and pricing optimization.

• Technologies used:Developed a Streamlit-based app integrating PandasAI and OpenAI's GPT-3.5, enabling users to upload CSV files, ask data-driven questions , and perform operations using natural language queries along with Python, OpenAI GPT-3.5(LLM) , PandasAI,Pandasai.llm, Pandas,OpenAI Api key and Streamlit.

• Technologies used : Plotly, Dash, Bootstrap, pip It is created by using Dash (a Python framework) and some ML models, ML models will enable the user to get predicted stock prices for the data inputted by the user.