Cholakov It Development Services

23/06/2025

In this seminar hosted by SoftUni, I walk you through some of the most powerful concepts behind building modern AI agents using LangChain.🔍 From building RA...

02/03/2025

https://www.youtube.com/watch?v=Ssu_YeeITOI
🚀 Weaviate: The Open-Source Vector Database for Hybrid Search & AI
In this video, we explore Weaviate, an advanced open-source vector database designed for hybrid search, retrieval-augmented generation (RAG), semantic search, and recommendation systems. Unlike Pinecone (fully managed) or Qdrant (optimized for ANN search), Weaviate combines structured data, keyword search, and vector search into a powerful AI-driven system.
🔹 What You’ll Learn:
✅ Weaviate’s Storage Engine – How it handles real-time vector search and structured data.
✅ Indexing Algorithms – HNSW, BM25, hybrid search, and reranking models.
✅ Built-in Similarity Metrics – Cosine, Dot Product, L2-Squared, Hamming, Manhattan.
✅ Optimizations & Benefits – Schema-based storage, multi-tenancy, and real-time updates.
✅ Weaviate Use Cases – RAG (Retrieval-Augmented Generation), e-commerce search, multimodal retrieval.
✅ Comparison – Weaviate vs Pinecone vs Qdrant: Which one is right for you?
🔗 Learn More on My Website:
💡 If you found this helpful, don’t forget to:
👍 Like the video | 🔔 Subscribe for more AI & vector database content!
📌 Hashtags for Search Optimization:

🚀 Weaviate: The Open-Source Vector Database for Hybrid Search & AIIn this video, we explore Weaviate, an advanced open-source vector database designed for h...

23/11/2024

Saving and Loading PyTorch Models | Recommendation System Tutorial #5

In this video, learn how to save and load PyTorch models effectively—a crucial skill for deploying and continuing training your neural networks. This is the fifth video in our series on building a recommendation system with Python, PyTorch, and Pandas.

📂 GitHub Repository: https://github.com/cholakovit/recommendation_system

🌐 Visit My Website: https://cholakovit.com

Make sure to check out the earlier videos in this series to follow along with the complete recommendation system project. Don't forget to like, subscribe, and share your thoughts in the comments below!

https://www.youtube.com/watch?v=r-CsrhT9E80&ab_channel=cholakovit

"Welcome to the fifth video in our series on building recommendation systems with Python, PyTorch, and Pandas! 🎉In this tutorial, we explore how to save and...

04/11/2024

https://www.youtube.com/watch?v=TJrn5HjBKSI&ab_channel=cholakovit
Welcome to Part 5 of our Recommendation System series! In this video, we dive into training and validating our recommendation model using PyTorch. I’ll walk you through the purpose and structure of the Trainer class, explaining each part of the train and validate methods step-by-step.

Welcome to Part 5 of our Recommendation System series! In this video, we dive into training and validating our recommendation model using PyTorch. I’ll walk ...

31/10/2024

https://www.youtube.com/watch?v=FLjbOMPPFuk&ab_channel=cholakovit
Learn how to build a PyTorch-based recommender system with a class structure for item recommendations, optimized for CPU and GPU. In this video, we go through the code, explain each line, and show how to make recommendations using a trained model. Perfect for those interested in deep learning and recommendation systems!

Learn how to build a PyTorch-based recommender system with a class structure for item recommendations, optimized for CPU and GPU. In this video, we go throug...

20/10/2024

https://www.youtube.com/watch?v=84tp2aBB0gc&ab_channel=cholakovit
Welcome to this tutorial where I’ll walk you through building a PyTorch recommendation system. In this project, we'll create a collaborative filtering model that learns from user-item interaction data, like movie ratings or product preferences and makes personalized recommendations. We’ve structured the application for simplicity and modularity, separating data loading, model building, training, and prediction into different components. By the end of this video, you’ll understand how to design and implement a powerful recommendation engine using machine learning techniques. Let’s get started!

"Welcome to this tutorial where I’ll walk you through building a PyTorch recommendation system. In this project, we'll create a collaborative filtering model...

05/06/2024

https://cholakovit.com/en/blog/musc/accessibility

In today's digital age, ensuring your website is accessible to all users is not just a legal obligation but also a moral imperative. Accessibility goes beyond simply making your website usable; it involves creating an inclusive environment where everyone, regardless of their physical abilities, can interact with your content. Here are some best practices for improving web accessibility.

27/05/2024

https://cholakovit.com/en/blog/musc/security-express

Ensuring the security of a Node.js application involves implementing various security measures to protect against common vulnerabilities and attacks. This article highlights crucial security practices, tools, and configurations to secure your application effectively.

Learn key security practices, tools, and configurations to protect your Node.js applications from vulnerabilities and attacks. Implement effective security measures today.

29/04/2024

https://cholakovit.com/en/blog/mongodb/searching-items-tags
Search items based on tags

16/04/2024

https://cholakovit.com/en/blog/fetch-global-state-js/tanstack-react-query

Tankstack React Query

27/11/2023

https://cholakovit.com/en/blog/system-design/microservice-architecture

Microservices architecture is a software design approach where an application is broken down into small, independent, and loosely coupled services, each responsible for specific business functionalities, enabling easier development, deployment, and scalability.

React, NextJS, NodeJS, TypeScript, Go Lang, PHP, MySQL, PostgreSQL, MongoDB, HTML & CSS