During my internship, I focused on developing my Python skills.Key areas of my work included:-Object Oriented Programming (OOP): I have mastered the key principles of OOP in C++ such as classes, objects, inheritance, encapsulation andpolymorphism. This allowed me to create structured and reusable code.-Standard Template Library (STL): I learned various STL components such as containers (vector, list, map), algorithms (sort, reverse, find)and iterators.-Memory management: Worked with pointers and references, studied dynamic memory allocation using new and delete operators.-Exceptions: Familiar with the exception handling mechanism ni C++, learned how to create your own exception classes.-Multithreaded Programming: Practiced creating and managing threads.-Working with databases: Learned how to connect to and interact with databases using C++. Practiced working with SQL and ORM libraries.-Network Programming: Learned the basics of network programming, worked with sockets to create TCP/IP connections.

During my internship, I focused on developing my Python skills and exploring its applications in data science.-Python Basics: Learned Python syntax and fundamental programming concepts.-Clustering Algorithms: Worked with K-Means and K-Nearest Neighbors (KNN) for data clustering.-Regression Analysis: Conducted linear and non-linear regression analyses to interpret data relationships.-Data Visualization: Used Python's Matplotlib library for creating various types of data plots.-Python Modules: Gained proficiency in Pandas for data analysis and SciPy for scientific computing.-Color Detection Project: Developed a small project using the K-Means algorithm for color detection in images.

During my internship, I worked as a Java developer on a project aimed at creating and optimizing a system for object detection. This project was focused on developing efficient and accurate algorithms for detecting objects in various scenarios.Main Responsibilities and Projects:-Development of object detection algorithms in Java, including image analysis and processing.-Integration of the developed algorithms with the existing system to enhance its performance.-Testing the algorithms on various datasets to ensure their accuracy and efficiency.-Skills and Technologies Acquired:-In-depth study of Java and its application in the context of image processing and machine learning.-Experience with libraries for image processing and machine learning, such as OpenCV.-Familiarity with the basics of machine learning and its application to object detection tasks.