Catalog Search Results
Author
Pub. Date
2021
Language
English
Description
Get started with Github and Github Actions in this introductory video to GitOps concepts, by building a container, setting some Github Actions to prevent problems, and finally, push to DockerHub in a fully automated way. These concepts are critical to get automation best-practices in place with Github. Particularly useful when collaborating with others and trying to run automated checks on Dockerfiles and git repos. Topics include: * Create a new...
Author
Pub. Date
2020
Language
English
Description
This is a one hour introduction to Python with code samples you can execute at home at the same time. Code can be executed here: https://github.com/noahgift/functional_intro_to_python/blob/master/Public_Master_SafariOnline_Day1_Part1.ipynb Subscribe to YouTube channel: https://lnkd.in/gUpprB2 You can find more content by Noah Gift at https://noahgift.com. #pragmaticai #python #tutorial.
Author
Pub. Date
2021
Language
English
Description
Learn to use AWS Elastic Beanstalk to deploy a Flask application. This tutorial covers Continuous Delivery of a Python Flask application using AWS Code Build. Elastic Beanstalk is a PAAS (Platform as a Service) that has powerful tools and integrations. This video course covers building out an development environment in Cloud9, a Makefile system and then finally, a full fledged CI/CD pipeline using Pylint and AWS Code Build of a Flask API. Follow along...
Author
Pub. Date
2021
Language
English
Description
The Go programming language is becoming more popular these days with cloud-native applications and the Kubernetes ecosystem. If you are coming from Python, you will find yourself surprised to see similar patterns, while at the same time see some things that are missing or plain impossible with Go. In this course, I will introduce you to some of the basics of Golang from a Python perspective, so that you can reduce the friction trying to learn it....
Author
Pub. Date
2021
Language
English
Description
A walkthrough of Chapter 1 of the O'Reilly book Practical MLOps. Topics include: * DevOps * MLOps * DataOps * ML Platforms * Sagemaker * Continuous Integration and Continuous Deployment * MLOps cookbook * ML Engineering * Data Engineering * Spark * GCP * Azure * Containers * Kaizen.
Author
Pub. Date
2021
Language
English
Description
One of the important aspects of MLOps, also known as Machine Learning Operations or Operationalizing Machine learning, is to package ML models. How exactly do you package ML models? In this video I show you exactly what that means, and go through the process of packaging an ONNX model taken from the ONNX Model Zoo. I end up with a docker container that can be shared, exposing an API that is ready to consume and perform live predictions for sentiment...
Author
Pub. Date
2021
Language
English
Description
A walkthrough of Chapter 5 of the O'Reilly book Practical MLOps. Topics include: * Getting models into production * Feature Store vs Data Warehouse * AutoML * MLOps * DataOps * ML Platforms * Sagemaker * Continuous Integration and Continuous Deployment * MLOps cookbook * ML Engineering * Data Engineering * Spark * GCP * Azure * Containers * Kaizen.
Author
Pub. Date
2021
Language
English
Description
Get started with Google Cloud Platform (GCP) and Cloud Functions in this one-hour video. Everything you need to know to get up and running quickly using serverless technology from GCP. Topics include: * An introduction to serverless technologies * Create a cloud function, install dependencies, and use different runtimes like Python 3.8 * Debug issues when a cloud function deployment fails * Use Google's Machine Learning offering to do live translations...
Author
Pub. Date
2021
Language
English
Description
Learn to ruthlessly scrape data using APIs you discover as well as cut and paste. Topics include: * Business Analytics * Data Science * Google Colab * Jupyter * Scraping * Cut and Paste * Google Sheets * Cleaning Data * Using Pandas with found data * Using the Twitter and Pandas API.
Author
Pub. Date
2021
Language
English
Description
In this video you walk through foundational concepts in optimization and greedy algorithms. These concepts include: * Greedy algorithms * Operations Research * Linear Solvers * Traveling Salesman * Knapsack * No Code and Low Code Business Intelligence tools on AWS * AWS Data Brew * AWS Quicksight * AWS Lambda * Greedy Coin * Tensorflow Playground * Deep Learning intuition.
Author
Pub. Date
2021
Language
English
Description
Get started with security vulnerability scanning and integrating that with Github, Github Actions and automated security checks in pull requests. Learn how to scan reported vulnerabilities in projects and Docker containers, so that you can publish images to Docker hub or merge pull requests while knowing that changes in dependencies are secure. Topics include: * Install and run locally a security vulnerability scanner * Catalog a project with an SBOM...
Author
Pub. Date
2020
Language
English
Description
Get started with Cloud Computing in Python. Topics include: Multi-Cloud, Cloud Computing Service Models, Distributed Computing in the Cloud, Cloud Computing ETL Pipelines, Serverless Soutions with the Cloud, Containers in the Cloud, and Continuous Delivery for ML Engineers.
Author
Pub. Date
2021
Language
English
Description
Get started with MLOps and Github Actions to package a container with an ONNX model that does live inferencing with a Flask application. By using Azure ML, learn how to download the large ONNX model into the Github Action workflow, package it as a container and then push it to a container registry. For reference use the https://github.com/alfredodeza/flask-roberta repository Topics include: * Create a container that does live inferencing with Flask...
Author
Pub. Date
2021
Language
English
Description
Learn to use AWS App Runner to do an MLOps workflow that deploys a Flask Microservice that running sklearn. This tutorial walks you through how to deploy code from the O'Reilly book Practical MLOps using the AWS App Runner Service. Topics include: * MLOps * AWS App Runner * Container as a Service * Python * Flask * Microservice * Sklearn * Machine Learning Engineering.
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