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Hi my name is
Spas Cholakov
web developer.

Software Developer (Full Stack) / Data Scientist

React / NextJS / NodeJS / TypeScript / Golang / Python / PHP




React
5+ years
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NodeJS
5+ years
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GO Lang
2+ years
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PHP
14+ years
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Mongo DB
4+ years
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MySQL
14+ years
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Typescript
5+ years
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HTML & CSS
14+ years
Portfolio

People often ask me why I create these tutorials. For me, it’s about sharing the knowledge I’ve gained over the years and contributing something meaningful to the
community — a way to give back and inspire others on their journey!

VectorDB - Qdrant Explained

Vector DB

  • Qdrant | Storage Engine | Indexing Algorithms | Optimizations | Downsides & Trade-offs | Use Cases

MedInsights AI Tutorials with Python

Ready to dive into the world of AI in healthcare? 🚀 In this video, we'll build a powerful medical assistance API called Med Insights, which leverages AI to help doctors diagnose complex cases more efficiently. From data upload to AI-powered querying and generating insightful reports, you'll learn how to create an impactful AI application with Python.

  • Build an AI-Powered Medical Insights API with Python | Step-by-Step Tutorial #1

  • Flask vs FastAPI vs Django: Choosing the Best Framework for AI-Powered APIs #2

  • Master Python Web Servers: WSGI vs ASGI, Uvicorn, Daphne, Hypercorn, uWSGI Simplified! #3

  • Build an AI-Powered App with FastAPI, Qdrant, NumPy, and Pydantic | Step-by-Step Tutorial #4

  • Build an AI-Powered App with FastAPI, Qdrant, NumPy, and Pydantic | Step-by-Step Tutorial #5

  • Build an AI-Powered App with FastAPI, Qdrant, NumPy, and Pydantic | Step-by-Step Tutorial #6

  • Build an AI-Powered App with FastAPI, Qdrant, NumPy, and Pydantic | Step-by-Step Tutorial #7

  • Build an AI-Powered App with FastAPI, Qdrant, NumPy, and Pydantic | Step-by-Step Tutorial #8

  • Build an AI-Powered App with FastAPI, Qdrant, NumPy, and Pydantic | Step-by-Step Tutorial #9

Recommendation System Tutorials with Python

Explore my first video tutorials on building a recommendation system using Python. These videos cover essential tools like AI, PyTorch, and Pandas libraries. While the quality reflects my initial steps in creating tutorials, they provide valuable insights into building intelligent recommendation systems.

  • PyTorch DataLoader for Recommendation System: Loading and Preparing User-Item Data | Tutorial #1

  • Building a Recommendation System with Matrix Factorization | Python & PyTorch Tutorial #2

  • Optimizing PyTorch Recommendation Systems for CPU & GPU | Item Recommendation Tutorial #3

  • Training & Validating a PyTorch Recommendation Model | Tutorial #4

  • How to Save and Load Models in PyTorch | Recommendation Systems Tutorial #5

  • Building a AI, PyTorch Recommendation System | Tutorial #6

  • How to Build and Run a Neural Network with TensorFlow and Panda – Complete Tutorial