jpascoe

amazon-sagemaker-deployment-workshop

amazon-sagemaker-examples

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

amazon-sagemaker-feature-store-end-to-end-workshop

amazon-sagemaker-immersion-day

amazon-sagemaker-mlops-workshop

MLOps workshop with Amazon SageMaker

amazon-sagemaker-secure-mlops

amplify-nextjs-starter-app

This is a Next.js starter for building a fullstack app with AWS Amplify.

aws-cdk-lambda-layer-builder

jpascoe/amazon-sagemaker-examples

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

jpascoe/amazon-sagemaker-mlops-workshop

MLOps workshop with Amazon SageMaker

jpascoe/amazon-sagemaker-secure-mlops

jpascoe/amplify-nextjs-starter-app

This is a Next.js starter for building a fullstack app with AWS Amplify.

jpascoe/aws-cdk-lambda-layer-builder

jpascoe/aws-lambda-developer-guide

The AWS Lambda Developer Guide

jpascoe/aws-lambda-powertools-python

A suite of utilities for AWS Lambda Functions that makes distributed tracing, structured logging, custom metrics, idempotency, and many leading practices easier

jpascoe/aws-mlops-pipelines-terraform

MLOps on AWS using Amazon SageMaker Pipelines

jpascoe/aws-mlu-explain

Visual, Interactive Articles About Machine Learning: https://mlu-explain.github.io/

jpascoe/aws-mwaa-local-runner

This repository provides a command line interface (CLI) utility that replicates an Amazon Managed Workflows for Apache Airflow (MWAA) environment locally.

jpascoe/aws-native-observability-dashboard

The Next-Gen AWS Management Console. Grafana dashboards for deep observability into various AWS configurations and Serverless Insights.

jpascoe/aws-native-observability-exporters

These AWS Native exporters provide the necessary data to power the visualizations in the [AWS Native Cross-account Observability Dashboard] repository.

jpascoe/aws-well-architected-labs

Hands on labs and code to help you learn, measure, and build using architectural best practices.

jpascoe/deepracer-log-analysis

Adventures in a data-driven approach to training, evaluating and tuning AWS DeepRacer reinforcement learning models (compatible with the new AWS DeepRacer console training logs after Aug 2020).

jpascoe/erpnext

Free and Open Source Enterprise Resource Planning (ERP)

jpascoe/frappe_docker

Docker images for production and development setups of the Frappe framework and ERPNext

jpascoe/Gooey

Turn (almost) any Python command line program into a full GUI application with one line

jpascoe/hexyback-workshop

jpascoe/Lambda-Layers

A collection of AWS lambda layers for python.

jpascoe/lambdaedge-openidconnect-samples

jpascoe/machine-learning-engineering-for-production-public

Public repo for DeepLearning.AI MLEP Specialization

jpascoe/mlops-with-terraform-sagemaker-and-code-pipelines

jpascoe/mlops-workload-orchestrator

The MLOps Workload Orchestrator solution helps you streamline and enforce architecture best practices for machine learning (ML) model productionization. This solution is an extendable framework that provides a standard interface for managing ML pipelines for AWS ML services and third-party services.

jpascoe/ms-identity-javascript-react-spa

A React single-page application calling Microsoft Graph via Azure AD and MSAL React.

jpascoe/now-ui-kit-react

React version of Now UI Kit by Creative Tim

jpascoe/quota-monitor-for-aws

This solution leverages AWS Trusted Advisor and Service Quotas to monitor AWS resource usage and raise alerts.

jpascoe/sagemaker-studio-efs-recovery-serverless

jpascoe/serverless-libreoffice

Run LibreOffice in AWS Lambda to create PDFs & convert documents

jpascoe/software-dev-for-mlops-101

Set up your local environment to do some real Machine Learning Operations software development, just like pro MLOps practitioners.

jpascoe/tfc-workshops-sentinel

Sentinel policies for use in pre-sales workshops: https://hashicorp.github.io/workshops