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Julien Heiduk
Julien Heiduk

Julien Heiduk

Let's talk about recommandation systems and ML in real-world business scenarios.

GCN with PyTorch for Co-Purchase Recommendation

Graph Convolutional Networks turn co-purchase data into a graph and learn item embeddings for recommendation. A full PyTorch Geometric implementation included.

GCN with PyTorch for Co-Purchase Recommendation

Retrieval-Augmented Generation with LangChain

RAG grounds LLM answers in your own documents. Learn how to build a production-ready RAG pipeline with LangChain, FAISS, and OpenAI in Python.

Retrieval-Augmented Generation with LangChain

Model Context Protocol server with FastMCP

This tutorial explores how to create a MCP server with FastMCP and why use it.

Model Context Protocol server with FastMCP

Cleora part 2: How to create user embeddings?

This tutorial explores how to generate user embeddings from interaction data using Cleora, a high-performance graph embedding tool — ideal for recommendation systems and graph-based machine learning.

Cleora part 2: How to create user embeddings?

Cleora part 1: Graph Embeddings

In the realm of data science, understanding relationships among entities is critical. Cleora shines in this context by efficiently modeling relationships

Cleora part 1: Graph Embeddings