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Hi everyone,
As 2023 comes to an end, I would like to share with you a summary of my articles that I wrote this year. I published 8 articles on Medium (publication in Geek Culture), covering topics such as data science, natural language processing, semantic search, low-level models, and Copilot. In this summary, I will highlight some of the key technology trends I observed this year and make a forecast for the next year.
One of the main themes of my articles was how to leverage the power of data and artificial intelligence to create better products and services for customers. In my first article, I explored how we can use neural networks to model the human brain and learn from data in a more efficient and natural way. I also showed how we can use Azure OpenAI service to analyze customer reviews and generate insights and suggestions. In another article, I demonstrated how we can use Streamlit and Azure OpenAI service to create interactive web apps that use GPT-3 to generate natural language responses.
Another theme that I focused on was how to use word embeddings and vector databases to enhance product search and recommendation systems. Word embeddings are a way of representing words as numerical vectors that capture their semantic meaning and similarity. Vector databases are a type of database that allows us to store and query these vectors efficiently. In my articles, I showed how we can use these technologies to create more relevant and engaging product recommendations, as well as semantic…
