Mariya Mansurova

Building single- and multi-agent workflows with human-in-the-loop interactions Mariya Mansurova · Follow Published in Towards Data Science · 21 min read · 8 hours ago — Image by DALL-E 3 LangChain is one of the leading frameworks for building applications powered by Lardge Language Models. With the LangChain Expression Language (LCEL), defining and executing step-by-step action sequences — also known as chains — becomes much simpler. In more technical terms, LangChain allows us to create

Automating Routine Tasks in Data Source Management with CrewAI Mariya Mansurova · Follow Published in Towards Data Science · 26 min read · 10 hours ago — Image by DALL-E 3 Initially, when ChatGPT just appeared, we used simple prompts to get answers to our questions. Then, we encountered issues with hallucinations and began using RAG (Retrieval Augmented Generation) to provide more context to LLMs. After that, we started experimenting with AI agents, where LLMs

Top 10 engineering lessons every data analyst should know Mariya Mansurova · Follow Published in Towards Data Science · 16 min read · 7 hours ago — Image by DALL-E 3 The data analyst job combines skills from different domains: We need to have business understanding and domain knowledge to be able to solve actual business problems and take into account all the details. Maths, statistics, and fundamental machine learning skills help us perform rigorous

Part 3: Modelling Ops queues Mariya Mansurova · Follow Published in Towards Data Science · 23 min read · 19 hours ago — Image by DALL-E 3 Today, I would like to show you an example of the discrete-event simulation approach. We will model the Customer Support team and decide what strategy to use to improve its performance. But first, let me share a bit of my personal story. I first learned about discrete simulations

Part 1: Task-specific approaches for scenario forecasting Mariya Mansurova · Follow Published in Towards Data Science · 20 min read · 3 hours ago — Image by DALL-E In product analytics, we quite often get “what-if” questions. Our teams are constantly inventing different ways to improve the product and want to understand how it can affect our KPI or other metrics. Let’s look at some examples: Imagine we’re in the fintech industry and facing new