Exploring the World of Fashion MNIST and CNNs at Intel 🌟Embarking on the Intel Unnati Industrial Training - Summer 2023 was a transformative journey into the realm of computer vision and deep learning. Under the expert mentorship of Dr. P Getzi Jeba Leelipushpam, I had the privilege of diving into the fascinating intersection of fashion and technology.During this immersive experience, I delved into the intricacies of Fashion MNIST – a dataset of grayscale fashion images. Guided by my curiosity, I harnessed the power of Convolutional Neural Networks (CNNs) to create an efficient model that achieved an impressive 91.92% accuracy in classifying various clothing items.From meticulously preparing the dataset to fine-tuning hyperparameters, and even exploring Intel's optimization techniques to enhance inference speed, every step was a new lesson and a fresh perspective. This experience not only expanded my technical skill set but also fostered a deeper passion for using AI to solve real-world challenges.📊 Tech Stack: Python, TensorFlow, OpenVINO

During this internship, I gained hands-on experience in various aspects of web development, focusing on full stack technologies. I worked extensively with HTML, CSS, and JavaScript to create visually appealing and interactive user interfaces. Additionally, I utilized MySQL for database management and Node.js along with Express.js for server-side development.Throughout my internship, I actively participated in developing and deploying web applications, contributing to the team's success. I also took the initiative to enhance my skills and started learning React, a popular JavaScript library for building user interfaces. This exposure allowed me to understand the concepts and best practices associated with React development.The internship at Paladin Software Solutions was a valuable learning experience, enabling me to strengthen my technical abilities and collaborate effectively in a professional setting.

Internship in Fundamental of Machine Learning with Python for Business & Data Analyticsat YBI Foundation. During this Internship, I had the opportunity to work on a project titled "Hand Written Digit Prediction - Classification Analysis." The main objective of the project was to analyze a dataset consisting of 8x8 pixel images of digits and use machine learning techniques to predict the digit each image represents.During this Internship, I worked with the Python programming language and utilized various libraries such as NumPy, Pandas, and Scikit-learn to preprocess the data, build the classification model, and evaluate its performance. Through this project, I gained a deep understanding of data preprocessing techniques, model building and evaluation, and the importance of data visualization in machine learning.

In this Internship the task required implementing a program that takes user-input IPv4 addresses, performs validation and conversion of the addresses to their binary, octal, and hexadecimal formats using built-in libraries or functions, stores the results in a list, and writes the output to a file . This involves understanding network protocols, programming languages, debugging, and efficient coding techniques.