Build a private AI Report Generator from Excel using Ollama to turn Excel charts into PowerPoint slides with local AI insights, while keeping your data on your own machine.
Chrome downloaded a 4GB local AI model file called weights.bin on my PC. Here is what I found, why Gemini Nano exists inside Chrome, and the bigger question about hidden AI downloads, user control, and transparency.
Learn how to use Gemma 4 with Ollama and Streamlit to build a private local image renaming workflow. This guide shows how to analyze images, generate filename suggestions, and keep the full process on your own machine.
Learn how to build a local RAG with Ollama pipeline using your own documents. This step-by-step guide covers chunking, embeddings, cosine similarity, and retrieval, showing how Mistral can answer questions about recent events using only local data.
Tokenization is the first step that allows AI models to read and understand text. In this post, we break down how tokenization works, why it matters, and how text becomes machine-readable, using simple explanations and a practical Python example
Learn how to build a private AI data analyst using PandasAI and Ollama. This step-by-step guide shows how to run data analysis locally, keep your data secure, and create an interactive interface with Streamlit — all without relying on cloud APIs.
Build an AI Excel Formula Generator in Python using Hugging Face T5. Learn how to turn plain English into working Excel formulas such as VLOOKUP, IF, and SUMIF — step by step.
Your complete guide to understanding the language of artificial intelligence. This glossary breaks down complex AI and Machine Learning terms into simple, clear definitions.
Fine tuning a powerful base model is key for challenging tasks. In this guide, we adapt InceptionV3 for high-accuracy car recognition on the Stanford Cars dataset.
Practical Transfer Learning with ResNet50: build the pipeline, control overfitting, and evaluate on Stanford Cars with accuracy curves and a confusion matrix—no fine-tuning