mandiant /
thiri-notebook
The Threat Hunting In Rapid Iterations (THIRI) Jupyter notebook is designed as a research aide to let you rapidly prototype threat hunting rules.
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hemantdpatil / repository
Designed a prototype of a market basket analytics system, look at the products the customer has in their online shopping cart and recommend another product.
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Designed a prototype of a market basket analytics system, look at the products the customer has in their online shopping cart and recommend another product.
Selected from shared topics, language and repository description—not editorial ratings.
mandiant /
The Threat Hunting In Rapid Iterations (THIRI) Jupyter notebook is designed as a research aide to let you rapidly prototype threat hunting rules.
27/100 healthjlee17 /
The Intel® DevCloud for the Edge allows you to actively prototype and experiment with AI workloads for computer vision on Intel hardware. This repository contains a series of Jupyter* notebook tutorials and examples hosted on Intel® DevCloud for the Edge. It comes preloaded with everything you needed to quickly get started. This includes trained models, sample data and executable code from the Intel® Distribution of OpenVINO™ Toolkit as well as other tools for deep learning. These notebooks are designed to help you quickly learn how to implement deep learning applications to enable compelling, high-performance solutions.
30/100 healthkhubaibarif25 /
A Jupyter Notebook solution where sellers log in, create customer profiles, select packages, record payments, and auto-update service status. Designed to map easily into Frappe DocTypes for a full web app.
34/100 healthanasingh2021 /
A collection of intermediate-level AI product prototypes built with Jupyter notebooks, covering multi-agent systems, RAG workflows, evaluation frameworks, fine-tuning concepts, and end-to-end AI feature demos. Designed for fast experimentation and communicating feasibility with engineering teams.
34/100 healthAyanBis /
An AI-powered agricultural support system designed to assist farmers with crop guidance, fertilizer recommendations, basic disease insights, and data-driven advisory using machine learning and structured decision logic. Includes exploration, analysis, and prototype workflows documented through a Jupyter Notebook.
34/100 healthmohakamitpatel /
A simple and interactive command-line tool that automates essential data preprocessing steps in machine learning workflows — including handling missing values, encoding categorical variables, and scaling features. Designed for beginners and rapid prototyping without needing Jupyter Notebooks.
27/100 health