In this article, you'll learn how to build a smart resume analyzing application using the DeepSeek R1 open-source GenAI LLM model and save operation costs.
Up to 70% of prompts in LLM applications are repetitive. Prefix caching can reduce inference costs by up to 90%, thus optimizing performance and saving money.
In this post, we will write a basic DNN using simple Python. To do that, we need to understand automatic differentiation and then implement it in code.
A brief introduction to Apache Cassandra for retrieval-augmented generation using Python and Ollama for developing applications free of cost locally or on a server.
Learn how to build MCP servers to extend AI capabilities. Create tools that AI models can seamlessly integrate, demonstrated through an arXiv paper search implementation.
In this article, learn how to use LLMs for web scraping with ScrapeGraphAI, LangChain, and Pydantic. This guide covers setup, configuration, and data extraction
This article discusses building an efficient ML pipeline with PySpark, covering data loading, preprocessing, model training, and evaluation for large datasets.
The Simulated Annealing algorithm described in this article demonstrates its effectiveness as a powerful tool for finding optimal solutions to complex problems.
Apply vector search and RAG experiments to enhance query results and optimize data storage for text embeddings, specifically with Bruce Springsteen's album data.
Tricentis Tosca's Vision AI simplifies UI testing with mockup-based test creation, self-healing capabilities, and built-in accessibility checks for dynamic applications.