Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Example notebooks for working with SageMaker Studio Lab. Sign up for an account at the link below!

Jupyter Notebooks in S3 - Jupyter Contents Manager implementation

Nighthawk Pages 3.0. This is a GitHub Pages project that includes support for Jupyter Notebooks. The project provides a game, lessons and projects to support the teaching of Career Technical Educations and AP courses: Computer Science and Software Engineering (CSSE), Computer Science Principles (CSP), and Computer Science A (CSA).

Tools to run Jupyter notebooks as jobs in Amazon SageMaker - ad hoc, on a schedule, or in response to events

machine learning for genomic variants

SageMakerで機械学習モデルを構築、学習、デプロイする方法が学べるNotebookと教材集

Cloud-ops automation runbooks that are ready to use. Build your own automations using the hundreds of drag and drop actions included in the repository. Built on Jupyter Notebooks, our automation platform jumpstarts your SRE RunBook creation. 😎 published by the unSkript community.

Kubernetes on AWS EKS

Jupyter notebooks and AWS CloudFormation template to show how Hudi, Iceberg, and Delta Lake work

This repo contains sample code and sample notebooks to illustrate how to work with Amazon FinSpace

A continuous integration (CI) system for 📓 Jupyter notebooks, built using 🧠 Amazon SageMaker.

This repo contains information regarding cloud offerings of OpenVINO™ and demos to showcase OpenVINO™ via sample Jupyter notebooks.

This repository contains some sample notebooks illustrating the use of DataRobot and SageMaker

Juptyer notebook tutorials on using the data in the AWS pacific-sound registry for ocean soundscape research, education, and the arts

This project shows step-by-step guide on how to build a real-world flower classifier of 102 flower types using TensorFlow, Amazon SageMaker, Docker and Python in a Jupyter Notebook.

It's just a terraform code for build a sagemaker notebook instance infrastructure to an AWS account. The code created a sagemaker notebook instance and needful things with a click. Maybe it's helpful to ML/DE Engineers.

❤️ Bits of Wisdom, Bytes of Code: Share, Learn, and Grow Together!

This repo contain example notebooks with instructions on using Intel AI Software listed in AWS SageMaker Marketplace.