Artificial Intelligence with Python: Libraries, Uses and Tools
Discover how to use Python for AI: libraries, examples, tools and real applications explained clearly and in depth.
Python
There is little to introduce to Python. It is well known by all developers.
Anything you want can be done with Python and this, together with its simplicity and simplicity, has made it one of the star programming languages today. It is a strongly typed object-oriented language in which it is especially important to maintain code readability.
It is the star language in data science, machine learning, deep learning, and everything related.
But you can still build web applications, or any other tool you can think of.
There are bookstores for everything!!!
In this section we solve some of the main problems that the Python developer often faces. In this way the way to become a ninja dev in python is assured.
Programmer’s Guide to Python Data and JSON
Learn how Python handles JSON: mapping types, parsing, pretty printing, files, and APIs with the json module in practical detail.
FastAPI project structure and best-practice guides
Learn how to structure FastAPI projects, from folder layouts to async, security and testing best practices, with real-world patterns.
AI Hallucinations: Why Smart Models Still Make Things Up
Discover why AI hallucinations happen, real examples, their risks and the best current techniques to detect and reduce them.
Developer guide to multi‑agent patterns with ADK
Learn key multi‑agent patterns in ADK, from Sequential to Parallel workflows, and how to run them reliably on Google Cloud.
Gemini 3 API updates, models and migration guide
Discover all Gemini 3 API updates, new models, tools and best practices to migrate and build powerful multimodal agents.
Open‑Source Language Model Evaluation Platforms Explained
Discover the key open‑source and enterprise platforms to evaluate, monitor and govern modern language models and LLM agents.
How to Host Language Models on a Low Budget
Learn how to host powerful language models on a tight budget, comparing APIs, cloud GPUs and local setups to cut costs without losing performance.
Prompt engineering for outlier detection in AI and data analysis
Learn how to design prompts that spot anomalies, secure LLMs and improve robust outlier detection in real‑world data.