I have completed my Ph.D. in Machine learning and Natural Language Processing. I have almost 10 years of teaching and development experience. I have worked on real-time LLM, Machine Learning, Deep learning, and Natural Language Processing problems. I have done a lot of projects, such as:
1-Stock Prediction Application: A qt5 desktop application which can predict the maximum profit entry point and exit point for a company's stock using different machine learning and deep learning techniques. The application showed the stocks listed in NASDAQ, NYSE and TSX. The user can add different companies' stocks to its list and apply different machine learning and deep learning techniques at three different time frames(short, medium and long). The user can adjust the parameters to the machine learning and deep learning methods to optimize them. The application showed different graphs. The application also visualized the performance of the applied methods with acutal results to show the accuracy of the applied methods. The application was also able to buy and sell the stocks listed in the user's owned stock. This was developed using pyQt.
2-Product Recommendation System: Developed a product recommendation system for an e-commerce bussiness using ML and deep learning techniques. The system filtered and predicted products that a user was most likely to purchase or be interested in.
3-Tweet Miner: Collecting, Storing, and Visualizing Real Time Twitter Data in Various Graphical Formats. I developed a Django application with elasticsearch and MongoDB as databases for storing real time tweets, along with a shiny R application for network graph visualization. Real-time tweets were collected using the Twitter API.
4-Web Scraping: Scraped ecommerce (TAOBAO, AliBaba 1688, etc), brewery (Don Julio, 1800 Tequila, etc.), betting, telegram channels, facebook posts, linkedin, Indeed, and different sites using their own API or by using Selenium, Scrapy, Beautifulsoup, Capybara, Guzzle, Cheerio, puppeteer, PhantomJS, and goutte.
5-ChatBots: Developed different types of chatbots like Question and Answers, Menu/button-based, Rule-Based, Keyword recognition-based, Machine learning-based, voice-based, appointment scheduling, Booking or customer support using different frameworks RASA, tidio, Chatfuel, Ada, Verloop, LiveChat, etc.
6-Machine Learning in Restaurants:Developed mobile applications, web applications, and machine learning and deep learning models that would help restaurants and diners to increase their sales, reduce their expenditure, create new menu items, enable quicker service, detect food safety and quality management in kitchen, etc.