Machine Learning Computer Science

Medhini C U

Bengaluru, ******

+91-872**-***** ************@*****.*** www.linkedin.com/in/medhini-udaya Career Objective

As a Computer Science and Engineering (CSE) student, I am passionate about advancing my skill set and striving for continuous improvement. My ambition drives me to make meaningful contributions, leveraging my skills and knowledge to achieve success. I am committed to applying my efforts in a way that creates a positive impact. Education

PES Institute of Technology and Management – VTU Shimoga, India Bachelor’s of Engineering, Computer Science & Engineering Aug 2019 – May 2023 Acharya Pre-University College – Karnataka Board Shimoga, India Science Jun2017 – May2019

Vikasa High School – Karnataka Board Shimoga, India Academic Institution April 2017

Technical Expertise

Programming and Operating Systems: Python, Java, Windows, HTML, CSS Skills and Tools: Data Structures and Algorithms, OOPS, MySQL. Tools/IDE: Eclipse, Visual Studio Code.

Technical Summary

Strong understanding of object-oriented programming principles.

Good understanding of RDBMS concepts, dependency, and normalization.

Proficient in writing SQL statements like DDL, DML, and DQL. Projects

Oral Cancer Detection and Classification Using Deep Learning

LabelImg, CVAT, or VGG Image Annotator (VIA), TensorFlow/Keras, PyTorch, ONNX, VGG, ResNet, Inception, or EfficientNet, Vision transformers (ViT), U-Net, Mask R-CNN, or Deeplab, SHAP, LIME, or Grad-CAM, Streamlit or Gradio, AWS, Azure, or Google Cloud, TensorFlow Lite or PyTorch Mobile, Docker, Flask or FastAPI, Dice Coefficient or IoU. Fake News Detection Using Machine Learning

BeautifulSoup, Scrapy, and Selenium (for collecting news data from websites).Convolutional Neural Networks (CNNs), Neural Networks (RNNs) or Long Short-Term Memory (LSTM), Flask/Django, FastAPI, AWS, Azure, or Google Cloud, Docker and Kubernetes, ROC-AUC, News APIs like NewsAPI, OpenAI APIs, or social media APIs for gathering news articles and user-generated content.

Human Activity Recognition Process Using 3-D Posture Data, Machine Learning

NumPy, Pandas, and SciPy, OpenCV, SciKit-Learn, PyTorch3D, LiDAR Sensors, Principal Component Analysis (PCA) or t- SNE, Long Short-Term Memory (LSTM) or Gated Recurrent Units (GRUs), DGL (Deep Graph Library) or PyTorch, Flask, FastAPI, or Django, TensorFlow Lite, ONNX, or NVIDIA TensorRT, AWS, Azure, or Google Cloud, MQTT or WebRTC. Certification

Completed Course on Full-Stack Development at KodNest, Bengaluru. Brief explanation about my course completion, I have embarked on an intensive journey into the realm of full-stack development focusing primarily on Java and Python technologies.(2023-2024)

Completed CSS & HTML Course from PREPINSTA.

Completed 5days workshop on “HACKERRANK BOOTCAMP” and got certificate.

Completed 2 months of course on “C, C++ & JAVA” organized by NES Institute.

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