Machine Learning and AI
- Machine Learning Model Development: developing and implementing machine learning models to extract insights and make predictions from data.
- Data Preprocessing and Feature Engineering: cleaning and optimizimh datasets, ensuring high-quality input for machine learning algorithms.
- Computer Vision: specialized in analyzing visual data, performing tasks like image classification and object detection.
- Deep Learning: developing and training complex neural networks for tasks like image recognition.
- Web Application Development using Flask, Django and FastAPI frameworks for building efficient and scalable web applications.
- Data Analysis and Machine Learning using NumPy, pandas, and scikit-learn, TensorFlow, Pytorch, OpenCV libraries for data analysis and machine learning tasks.
- Web Scraping using BeautifulSoup, Scrapy and Selenium libraries for web scraping and automated data extraction.
- Data Visualization using Matplotlib and Seaborn libraries to create visually appealing charts and graphs for effective data representation.
- .Desktop Application Development цith Windows Presentation Foundation (WPF) developing desktop applications with rich user interfaces. This includes creating visually appealing layouts, implementing interactive controls, and integrating with backend services and databases.
- Web Application Development using ASP.NET Core building robust and scalable web applications. This includes developing server-side logic, handling user requests, managing sessions, and integrating with databases using Entity Framework.