noahgift / Pragmaticai
Licence: other
[Book-2019] Pragmatic AI: An Introduction to Cloud-based Machine Learning
Stars: ✭ 79
Projects that are alternatives of or similar to Pragmaticai
Cloud Custodian
Rules engine for cloud security, cost optimization, and governance, DSL in yaml for policies to query, filter, and take actions on resources
Stars: ✭ 3,926 (+4869.62%)
Mutual labels: aws, serverless, azure, gcp
Datasciencevm
Tools and Docs on the Azure Data Science Virtual Machine (http://aka.ms/dsvm)
Stars: ✭ 153 (+93.67%)
Mutual labels: ai, azure, jupyter-notebook, ml
Examples
Infrastructure, containers, and serverless apps to AWS, Azure, GCP, and Kubernetes... all deployed with Pulumi
Stars: ✭ 1,085 (+1273.42%)
Mutual labels: aws, serverless, azure, gcp
Komiser
☁️ Cloud Environment Inspector 👮🔒 💰
Stars: ✭ 2,684 (+3297.47%)
Mutual labels: aws, serverless, azure, gcp
Pulumi
Pulumi - Developer-First Infrastructure as Code. Your Cloud, Your Language, Your Way 🚀
Stars: ✭ 10,887 (+13681.01%)
Mutual labels: aws, serverless, azure, gcp
Rpc Websockets
JSON-RPC 2.0 implementation over WebSockets for Node.js and JavaScript/TypeScript
Stars: ✭ 344 (+335.44%)
Mutual labels: aws, serverless, gcp
Terratag
Terratag is a CLI tool that enables users of Terraform to automatically create and maintain tags across their entire set of AWS, Azure, and GCP resources
Stars: ✭ 385 (+387.34%)
Mutual labels: aws, azure, gcp
Fastocloud
Self-hosted IPTV/NVR/CCTV/Video service (Community version)
Stars: ✭ 464 (+487.34%)
Mutual labels: ai, aws, ml
Docker Android
Android in docker solution with noVNC supported and video recording
Stars: ✭ 4,042 (+5016.46%)
Mutual labels: aws, azure, gcp
Terracognita
Reads from existing Cloud Providers (reverse Terraform) and generates your infrastructure as code on Terraform configuration
Stars: ✭ 452 (+472.15%)
Mutual labels: aws, azure, gcp
Awesome Ai Ml Dl
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.
Stars: ✭ 831 (+951.9%)
Mutual labels: ai, jupyter-notebook, ml
Mkit
MKIT is a Managed Kubernetes Inspection Tool that validates several common security-related configuration settings of managed Kubernetes cluster objects and the workloads/resources running inside the cluster.
Stars: ✭ 330 (+317.72%)
Mutual labels: aws, azure, gcp
Midway
🍔 A Node.js Serverless Framework for front-end/full-stack developers. Build the application for next decade. Works on AWS, Alibaba Cloud, Tencent Cloud and traditional VM/Container. Super easy integrate with React and Vue. 🌈
Stars: ✭ 5,080 (+6330.38%)
Mutual labels: aws, serverless, azure
Gbt
Highly configurable prompt builder for Bash, ZSH and PowerShell written in Go.
Stars: ✭ 457 (+478.48%)
Mutual labels: aws, azure, gcp
Cloudguardiaas
Check Point CloudGuard Network Security repository containing solution templates, Terraform templates, tools and scripts for deploying and configuring CloudGuard Network Security products.
Stars: ✭ 27 (-65.82%)
Mutual labels: aws, azure, gcp
Offensive Terraform.github.io
Offensive Terraform Website
Stars: ✭ 25 (-68.35%)
Mutual labels: aws, azure, gcp
Go Cloud
The Go Cloud Development Kit (Go CDK): A library and tools for open cloud development in Go.
Stars: ✭ 8,124 (+10183.54%)
Mutual labels: aws, azure, gcp
Arvados
An open source platform for managing and analyzing biomedical big data
Stars: ✭ 274 (+246.84%)
Mutual labels: aws, azure, gcp
Pragmatic AI: An Introduction To Cloud-based Machine Learning
Book Resources
This books was written in partnership with Pragmatic AI Labs.
You can continue learning about these topics by:
- Get the latest content and updates from Pragmatic AI Labs: Subscribe to the mailing list!
- Taking the course AWS Certified Cloud Practitioner 2020-Real World & Pragmatic.
- Buying a copy of Pragmatic AI: An Introduction to Cloud-Based Machine Learning
- Reading book online on Safari: Online Version of Pragmatic AI: An Introduction to Cloud-Based Machine Learning, First Edition
- Watching 8+ Hour Video Series on Safari: Essential Machine Learning and AI with Python and Jupyter Notebook
- Viewing more content at noahgift.com
- Viewing more content at Pragmatic AI Labs
- Exploring related colab notebooks from Safari Online Training
- Learning about emerging topics in Hardware AI & Managed/AutoML
- Viewing more content on the Pragmatic AI Labs YouTube Channel
- Reading content on Pragmatic AI Medium
- Attend an upcoming Safari Live Training
About
Pragmatic AI is the first truly practical guide to solving real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Writing for business professionals, decision-makers, and students who aren’t professional data scientists, Noah Gift demystifies all the tools and technologies you need to get results. He illuminates powerful off-the-shelf cloud-based solutions from Google, Amazon, and Microsoft, as well as accessible techniques using Python and R. Throughout, you’ll find simple, clear, and effective working solutions that show how to apply machine learning, AI and cloud computing together in virtually any organization, creating solutions that deliver results, and offer virtually unlimited scalability. Coverage includes:
- Getting and configuring all the tools you’ll need
- Quickly and efficiently deploying AI applications using spreadsheets, R, and Python
- Mastering the full application lifecycle: Download, Extract, Transform, Model, Serve Results
- Getting started with Cloud Machine Learning Services, Amazon’s AWS AI Services, and Microsoft’s Cognitive Services API
- Uncovering signals in Facebook, Twitter and Wikipedia
- Listening to channels via Slack bots running on AWS Lambda (serverless)
- Retrieving data via the Twitter API and extract follower relationships
- Solving project problems and find highly-productive developers for data science projects
- Forecasting current and future home sales prices with Zillow
- Using the increasingly popular Jupyter Notebook to create and share documents integrating live code, equations, visualizations, and text
- And much more
Book Chapter Juypter Notebooks
Note, it is recommended to also watch companion Video Material: Essential Machine Learning and AI with Python and Jupyter Notebook
- Chapter 1: Introduction to Pragmatic AI
- Chapter 2: AI & ML Toolchain
- Chapter 3: Spartan AI Lifecyle
- Chapter 4: Cloud AI Development with Google Cloud Platform
- Chapter 5: Cloud AI Development with Amazon Web Services
- Chapter 6: Social Power NBA
- Chapter 7: Creating an Intelligent Slack Bot on AWS
- Chapter 8: Finding Project Management Insights from A Github Organization
- Chapter 9: Dynamically Optimizing EC2 Instances on AWS
- Chapter 10: Real Estate
- Chapter 11: Production AI for User Generated Content (UGC)
License
This code is released under the MIT license
Text
The text content of notebooks is released under the CC-BY-NC-ND license
Additional Related Topics from Noah Gift
His most recent books are:
- Pragmatic A.I.: An introduction to Cloud-Based Machine Learning (Pearson, 2018)
- Python for DevOps (O'Reilly, 2020).
- Cloud Computing for Data Analysis, 2020
- Testing in Python, 2020
His most recent video courses are:
- Essential Machine Learning and A.I. with Python and Jupyter Notebook LiveLessons (Pearson, 2018)
- AWS Certified Machine Learning-Specialty (ML-S) (Pearson, 2019)
- Python for Data Science Complete Video Course Video Training (Pearson, 2019)
- AWS Certified Big Data - Specialty Complete Video Course and Practice Test Video Training (Pearson, 2019)
- Building A.I. Applications on Google Cloud Platform (Pearson, 2019)
- Pragmatic AI and Machine Learning Core Principles (Pearson, 2019)
- Data Engineering with Python and AWS Lambda (Pearson, 2019)
His most recent online courses are:
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].