Yashwanth Reddy Gadepally

Results-driven software engineer with a proven track record of developing robust and scalable solutions. Proficient in multiple programming languages and adept at collaborating with cross-functional teams to deliver high-quality software products. Strong problem-solving skills and a commitment to staying abreast of emerging technologies.

Covid-19 detection using Chest X-ray, Machine Learning
The Aim of the project is to detect Covid-19 using chest X-ray and obtained accuracy of 96.7%. Project purely relies on Convolutional Neural Network model (CNNs). Convolutional Neural Network-based model has been proposed for the detection of COVID infected patients using patient chest X-ray image (radiograph). The proposed model is developed to provide accurate diagnostics for binary classification (1 or 0). Our model produced a validation accuracy of 96.7% for binary classes.

Product Rating based on Reviews
The main objective of this project is to extract reviews of a product from a website, where users provide feedback for a product in the form of natural language. The algorithm that we utilized divides natural language into tokens, with each word having a positive or negative meaning and a rating of 1 to 5. It uses Natural Language Processing (NLP) to automatically rate the product based on the word's specified level of ratings. Automatically classify incoming support requests, evaluate customer interactions, and gauge customer mood. Utilize the information from client surveys to enhance your offerings.

Exploratory Data Analysis (EDA)
Exploratory Data Analysis (EDA) to check whether a country with more economic freedom has a better Human Development Index (HDI) or not. Aim of the project is to check correlation between human development index and economically free countries. Project learnings include Data Analysis, Data cleaning, Performing EDA, Business Reporting, Storytelling.

GitHub, Capstone Project

• https://github.com/Yash42ds/Yashwanth_Data606

ChatGPT Prompt Engineering for Developers, deeplearning.ai
• "Successfully achieved the task of completing the course from deeplearning.ai on ChatGPT Prompt Engineering for Developers."
• Proficient in working with large language models, leveraging their capabilities for natural language processing tasks.
• Experience in fine-tuning and adapting pre-trained language models to specific domains and applications.
• Skilled in using state-of-the-art models, such as GPT-3, BERT, or T5, to generate human-like text and assist in content creation.
• Strong understanding of the architecture and inner workings of large language models, enabling effective utilization and customization.
• Proven ability to develop chatbots, virtual assistants, and recommendation systems using language models for enhanced user experiences.
• Expertise in mitigating biases and ensuring ethical use of language models in AI application.