Learning methods

#programming #python #software #vscode #datascience

3-Layer Network

Most people start building AI projects by writing . py files. But sustainable, production-ready generative AI isn’t built on code alone. It’s built on structure. The biggest reason AI projects struggle isn’t lack of model accuracy —it’s poor architecture, organization, and maintainability. So I built a structured Generative AI Project Template → designed for scalability, modularity, and real-world production use. This isn’t just a folder layout. It’s a blueprint for building AI systems that...

See a step-by-step transformation of a messy data table into a clean, filterable dashboard. Watch the full video tutorial on our blog.

𝗧𝗵𝗶𝘀 𝗶𝘀 𝗵𝗼𝘄 𝗚𝗲𝗻𝗔𝗜 𝗳𝗶𝗻𝗱𝘀 𝗺𝗲𝗮𝗻𝗶𝗻𝗴 𝗶𝗻 𝘂𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝘁𝗲𝘅𝘁. ⬇️ And yes it all starts with vector databases — not magic. This is the mechanism that powers AI Agent memory, RAG and semantic search. And this diagram below? Nails the entire flow — from raw data to relevant answers. Let's break it down (the explanation shows of how a vector database works — using the simple example prompt: “Who am I): ⬇️ 1. 𝗜𝗻𝗽𝘂𝘁: ➜ There are two inputs: Data = the source text (docs, chat history, product...

One LEGO at a time: Explaining the Math of How Neural Networks Learn #neuralnetworks #machinelearning

Unlock the Power of AI Algorithms! From predicting stock prices 📈 to building chatbots 🤖, these top AI algorithms are the real engines behind innovation. 💡 Whether you’re in tech, business, or startups, mastering them gives you a massive edge in 2025! 👉 Which one do you think will dominate the future — Neural Networks or Reinforcement Learning? #AI #MachineLearning #DeepLearning #ArtificialIntelligence #DataScience #AIForBusiness #StartupLife #AIFuture #TechInnovation #AITools

Rotating Radar Device Simulation

What makes a data table great? Smart filtering. We break down the essential components for a smooth user experience. See the full anatomy guide on our blog.

10 Python Skills Every Developer Will Need Next Year

Transformer - more than meets the eye! Are we there yet? Well... not really, but... How about eliminating recurrence and convolution from transduction? Sequence modeling and transduction (e.g. language modeling, machine translation) problems solutions has been dominated by RNN (especially gated RNN) or LSTM, additionally employing the attention mechanism. Main sequence transduction models are based on RNN or CNN including encoder and decoder. The new transformer architecture is claimed...