Project: GIS with Folium

GIS partners recognised for exceptional achievement

A geographic information system (GIS) is a conceptualized framework that provides the ability to capture and analyze spatial and geographic data. GIS applications (or GIS apps) are computer-based tools, that allow the user to create interactive queries (user-created searches), analyze spatial information output, edit data presented within maps, and visually share the results of these operations.

Geographic information science (or, GIScience)—the scientific study of geographic concepts, applications, and systems—is commonly initialized as GIS, as well.

Geographic information systems are utilized in multiple technologies, processes, techniques, and methods. It is attached to various operations and numerous applications, that relate to engineering, planning, management, transport/logistics, insurance, telecommunications, and business. For this reason, GIS and location intelligence applications are at the foundation of location-enabled services, that rely on geographic analysis and visualization.

Let's look at the project at the Kaggle site: https://www.kaggle.com/samansiadati/gis-with-folium

Comments

Artificial Neural Network

Artificial neural networks (ANN) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains. The data structures and functionality of neural nets are designed to simulate associative memory. Neural nets learn by processing examples, each of which contains a known "input" and "result," forming probability-weighted associations between the two, which are stored within the data structure of the net itself. (The "input" here is more accurately called an input set, since it generally consists of multiple independent variables, rather than a single value.) Thus, the "learning" of a neural net from a given example is the difference in the state of the net before and after processing the example. After being given a sufficient number of examples, the net becomes capable of predicting results from inputs, using the associations built from the example set. If a feedback loop is prov...

Which AWS Certifications Exist for AI? A Practical Map

If you want to prove you can work with AI on AWS, the certification catalog can feel crowded. This post gives you a map: which credentials are aimed at AI, who each one is for, what the exams look like, and in which order a sensible person would take them. Every figure below comes from the official AWS certification pages as they stood on 25 October 2026, so always double-check the live pages before you book anything. The short version Two certifications are built squarely around AI on AWS, and they sit at opposite ends of the difficulty scale: AWS Certified AI Practitioner (AIF-C01) is the foundational, concept-level exam. AWS Certified Generative AI Developer – Professional (AIP-C01) is the advanced, build-it-in-production exam. Around them sits a ring of neighbouring certifications that make good stepping stones, plus a newer business-focused AI credential and a set of hands-on "Demonstrated" credentials. At a glance Detail AI Practitioner GenAI Developer ...

Project: Heartbeat computing

In computer science, a heartbeat is a periodic signal generated by hardware or software to indicate normal operation or to synchronize other parts of a computer system. Usually, a heartbeat is sent between machines at a regular interval in the order of seconds; a heartbeat message. If the endpoint does not receive a heartbeat for a time—usually a few heartbeat intervals—the machine that should have sent the heartbeat is assumed to have failed. Heartbeat messages are typically sent non-stop on a periodic or recurring basis from the originator's start-up until the originator's shutdown. When the destination identifies a lack of heartbeat messages during an anticipated arrival period, the destination may determine that the originator has failed, shutdown, or is generally no longer available. Heartbeat messages may be used for high-availability and fault-tolerance purposes.

Data / AI Blog

Search This Blog