Dnyaneshwari Prasad Pawale

Intro

Hello! I'm Dnyaneshwari Prasad Pawale, a passionate and dedicated Computer Science student deeply committed to advancing technology through innovative solutions. I recently completed my Master of Science in Computer Science from the New York Institute of Technology, graduating with a GPA of 3.71. Prior to that, I earned my Bachelor of Engineering in Computer Science from Savitribai Phule Pune University, achieving a CGPA of 9.81. Throughout my academic journey, my profound interest in software design, development, artificial intelligence, machine learning, computer vision, and natural language processing has been the driving force behind my academic achievements and professional aspirations.

I am keen to secure a position that aligns with my computer science background or allows me to delve deeply into AI and machine learning. The advancement of generative AI is particularly fascinating to me, and I am eager to explore its potential in shaping the future of technology. I prioritize staying abreast of the latest innovations and am confident in my ability to leverage these advancements effectively.

For collaborations, discussions, or inquiries, please feel free to reach out to me. You can explore more about my projects and connect with me on GitHub and LinkedIn. I am excited about the opportunity to contribute to transformative technological advancements and look forward to connecting with like-minded professionals who share my passion for innovation and excellence.

Projects

Network Intrusion Detection using Autoencoders

In today's digital age, network security is paramount. This project focuses on using advanced machine learning techniques to enhance network intrusion detection systems (NIDS).

This project demonstrates the effectiveness of autoencoders in network intrusion detection. By learning the patterns of normal network traffic, the autoencoder can identify deviations that signify potential intrusions, thereby enhancing cybersecurity measures.

View this project on GitHub : Network-intrusion-Detection-using-Autoencoders

Flight Fare Predition and Analytics

This project focuses on predicting flight fares using a comprehensive dataset from Kaggle. The process involves extensive data preprocessing, feature engineering, and the application of multiple machine learning algorithms to achieve accurate fare predictions. The project demonstrates a solid understanding of data analysis, feature engineering, and machine learning model development. The final model, an XGBoost Regressor, achieved an impressive R2 score of 0.8605, showcasing its ability to make accurate flight fare predictions. This project not only highlights technical proficiency in data science and machine learning but also provides valuable insights into the factors influencing flight ticket pricing.

View this project on GitHub : Flight-Fare-Predition-and-Analytics

Exploratory Data Analysis on Tweet Data

This comprehensive project involves analyzing a dataset of 10,000 tweets from January 2020. The analysis encompasses various aspects of the tweets, such as the sources used to post them, the number of replied and quoted tweets, user statistics, sentiment analysis, word cloud generation, and more. Additionally, the project includes sentiment analysis to segregate COVID-19 related tweets from non-COVID-19 tweets, providing insights into public sentiment during the early stages of the pandemic.

The findings can be used to understand trends and patterns in Twitter usage during January 2020, particularly in relation to the early stages of the COVID-19 pandemic. The project demonstrates proficiency in data analysis, sentiment analysis, and data visualization using Python.

View this project on GitHub : EDA-on-Tweet-Data

Stock price prediction using GAN

This project aims to predict stock prices by combining historical stock data with sentiment analysis from Twitter. By leveraging Generative Adversarial Networks (GANs) and advanced sentiment analysis techniques, the model strives to deliver accurate predictions of stock price movements.

By integrating sentiment analysis with traditional stock data, the model offers valuable insights into stock market behavior, benefiting investors and financial analysts alike.This project highlights the potential of combining deep learning techniques with sentiment analysis for stock price prediction, showcasing an innovative approach to understanding and forecasting stock market trends.

View this project on GitHub : Stock-Price-Prediction-Using-GANs-with-Sentiment-Analysis

Best Deal Finder Application

Our website aims to provide users with the best deals available on the internet by comparing the prices of various products. By linking users to multiple websites and conducting real-time price searches, we ensure that product pricing is always current, delivering incredible and reliable offers. Our commitment is to offer the highest quality at the most competitive prices, making it easy and thrilling for users to find fantastic deals on products they love. Everyone wants to shop more wisely and spend less, and our platform facilitates this by offering the best prices on top products.

Key features of our platform include:
Search it up: Discover the best products and prices by exploring offers. You can find new items you’ll adore while searching for things you need.
Savings: Combine discounted prices with credit card discounts, points, and coupons you have. The bottom line is to always shop around for the best deals on the best goods.

View this project on Bitbucket : Best-Deal-Finder-App

Tour planning using Kruskal's Algorithm

Aim of the project is to visualize UNESCO World Heritage Sites within a specified country and compute a Minimum Spanning Tree (MST) to determine the optimal travel route to visit all these sites. The MST is calculated using Kruskal's algorithm, ensuring minimal travel distance between the sites.

This project effectively demonstrates the use of data processing, algorithm implementation, and visualization techniques to analyze and optimize travel routes for UNESCO World Heritage Sites within a specified country. The approach ensures minimal travel distance, making it a valuable tool for travelers and researchers alike.

View this project on GitHub : Tour-Planner-using-Kruskal-s-Algorithm

Car Customization Application using Augmented Reality

The Car Customization Application is an advanced AR tool designed to enhance car customization using ARFoundation in Unity. Leveraging the ARCore XR Plugin for Android, it offers a rich set of AR functionalities. The application uses the device's camera to provide a live feed, acting as the AR camera. It performs plane detection to create GameObjects for each detected plane, allowing markerless placement of virtual car parts or accessories. Users can place, scale, and rotate virtual objects in the real environment. The rendering component combines the live camera feed with virtual objects, providing a realistic preview of the customized car. This application showcases advanced AR capabilities, enabling users to visualize and interact with car customizations in their real environment, highlighting expertise in AR development and practical applications of AR technology to enhance user engagement and satisfaction.

View this project on GitHub : Car-Customization-Application-using-Augmented-Reality

Food Bank Management System

View this project on GitHub : Food-Bank-Management-System

Skills

Languages

Python, C++, C, HTML, CSS, MySQL, R

Machine Learning, Artificial Intelligence

With a fervent passion for AI and ML, I am dedicated to continuously honing my skills through hands-on projects and practical applications. From developing robust fraud detection systems to crafting immersive AR experiences, I am eager to delve deeper into cutting-edge technologies, driven by a strong desire to innovate and solve real-world challenges using advanced machine learning techniques.

Software Development

As a fresher in software development, I bring a foundation in programming languages like Python, Java, and C++, coupled with a solid grasp of fundamental concepts in object-oriented programming, data structures, and database management. I am enthusiastic about applying my knowledge to create efficient and scalable solutions, eager to learn and adapt to new technologies while contributing effectively to innovative projects and team goals.

Development

Linux, Windows, Virtual Machines, Docker, Anaconda, Numpy, MatPlotLib, Pandas, Keras, PyTorch, Tensorflow, GPT, Generative AI Tools

Project Management

Git, GitHub, Jupyter Notebooks, Presentation Skills, Team Leadership/Management

Related Courses

Data Structures and Algorithms, Artificial Intelligence, Machine Learning, Computer Organization and Architecture, Operating Systems and security, Software Engineering, Data Mining, Big Data Analytics, Theory of Computations, Programming Languages, Database Management Systems

Interests

Data Science, Data Analytics, Cyber-Security, Generative AI, Blockchain, Augmented Reality, Virtual Reality

Resume

Contact

• GitHub
• LinkedIn
• Facebook
• Instagram

Elements

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