WorldCat Identities

Gift, Noah

Overview
Works: 94 works in 214 publications in 1 language and 5,871 library holdings
Genres: Study guides 
Roles: Author, Contributor
Classifications: QA76.585, 005.133
Publication Timeline
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Most widely held works by Noah Gift
Python for Unix and Linux system administration by Noah Gift( )

18 editions published in 2008 in English and held by 361 WorldCat member libraries worldwide

A guide to using the Python computer language to handle a variety of tasks in both the Unix and Linux servers
Pragmatic AI : an introduction to cloud-based machine learning by Noah Gift( )

11 editions published between 2018 and 2020 in English and held by 301 WorldCat member libraries worldwide

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 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, readers find simple, clear, and effective working solutions that show them how to apply machine learning, AI and cloud computing together in virtually any organization, creating solutions that deliver results, and offer virtually unlimited scalability. -- Provided by publisher
Python for DevOps : learn ruthlessly effective automation by Noah Gift( )

10 editions published between 2019 and 2020 in English and Undetermined and held by 263 WorldCat member libraries worldwide

"Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today's most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you'll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide."--
Python command line tools : design powerful apps with Click by Alfredo Deza( )

5 editions published in 2020 in English and Undetermined and held by 169 WorldCat member libraries worldwide

Presenting the simplest and most powerful UI ever invented, the command-line, this book teaches you the skills you need to master creating Python command line tools using the Click framework. --
Optimization and Greedy Algorithms in One Hour by Alfredo Deza( Visual )

6 editions published in 2021 in English and held by 138 WorldCat member libraries worldwide

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
Cloud Computing for Data Analysis by Noah Gift( )

3 editions published in 2020 in English and held by 136 WorldCat member libraries worldwide

This book is designed to give you a comprehensive view of cloud computing including Big Data and Machine Learning. Many resources will be used including interactive labs on Cloud Platforms (Google, AWS, Azure) using Python. This is a project-based book with extensive hands-on assignments. Based on material taught at leading universities
Pragmatic AI and machine learning core principles : LiveLessons by Noah Gift( Visual )

2 editions published between 2019 and 2020 in English and held by 126 WorldCat member libraries worldwide

"Shore up the foundational knowledge necessary to work with Artificial Intelligence and Machine Learning! This LiveLesson video covers the core principles of Artificial Intelligence and Machine Learning, including how to frame a problem in terms of Machine Learning and how Machine Learning is different than statistics. Learn about fundamental concepts including nearest neighbors, decision trees, and neural networks. The video wraps up covering timely machine learning topics such as cluster analysis, dimensionality reduction, and social networks."--Resource description page
Testing In Python Video Course by Noah Gift( Visual )

3 editions published in 2020 in English and held by 125 WorldCat member libraries worldwide

Noah and Alfredo have decades of experience testing with Python in major production environments. They are the authors of the book Testing in Python and Python for DevOps (O'Reilly). Learn from the best on how to get started and advance your automation with easy examples and code to follow up
Essential Machine Learning and AI with Python and Jupyter Notebook by Noah Gift( Visual )

3 editions published between 2018 and 2019 in English and held by 125 WorldCat member libraries worldwide

8+ Hours of Video Instruction Learn just the essentials of Python-based Machine Learning on AWS and Google Cloud Platform with Jupyter Notebook. Description This 8-hour LiveLesson video course shows how AWS and Google Cloud Platform can be used to solve real-world business problems in Machine Learning and AI. Noah Gift covers how to get started with Python via Jupyter Notebook, and then proceeds to dive into nuts and bolts of Data Science libraries in Python, including Pandas, Seaborn, scikit-learn, and TensorFlow. EDA, or exploratory data analysis, is at the heart of the Machine Learning; therefore, this series also highlights how to perform EDA in Python and Jupyter Notebook. Software engineering fundamentals tie the series together, with key instruction on linting, testing, command-line tools, data engineering APIs, and more. The supporting code for this LiveLesson is located at http://www.informit.com/store/essential-machine-learning-and-ai-with-python-and-jupyter-9780135261095 . About the Instructor Noah Gift is lecturer and consultant at UC Davis Graduate School of Management in the MSBA program. He is teaching graduate machine learning and consulting on Machine Learning and Cloud Architecture for students and faculty. He has published close to 100 technical publications, including two books on subjects ranging from Cloud Machine Learning to DevOps. He is also a certified AWS Solutions Architect and an SME (Subject Matter Expert for Machine Learning for AWS). He has an MBA from UC Davis, an MS in Computer Information Systems from Cal State Los Angeles, and a BS in Nutritional Science from Cal Poly San Luis Obispo. Professionally, Noah has approximately 20 years of experience of programming in Python and is a member of the Python Software Foundation. He has worked in roles ranging from CTO, General Manager, Consulting CTO and Cloud Architect. This experience has been with a wide variety of companies including ABC, Caltech, Sony Imageworks, Disney Feature Animation, Weta Digital, AT&T, Turner Studios, and Linden Lab. In the past ten years, he has been responsible for shipping many new products at multiple companies that generated millions of dollars of revenue and had global scale. He is the founder of Pragmatic AI Labs, a training, consulting, and AI/ML product company that specializes in cloud native Machine Learning and AI Solutions. Skill Level Beginner What You Will Learn Introduces Data Science concepts and Python funda
Python Functions Video Course by Alfredo Deza( Visual )

2 editions published in 2020 in English and held by 124 WorldCat member libraries worldwide

Many people wrongly believe that to program properly in Python, it is necessary to master all of its many moving parts. But the single most important part of modern Python programming - the part you should learn first - is the function. What can you do with a function? Build command-line tools, web applications, GPU programming, serverless, distributed computing, and machine learning. In the cloud and machine learning era, the function rules. In this course, you'll begin your Python journey through learning about this critically important subset of the Python language. You'll master the use of functions much more quickly by not getting bogged down with all the rest
Github Actions and GitOps in One Hour Video Course by Alfredo Deza( Visual )

2 editions published in 2021 in English and held by 123 WorldCat member libraries worldwide

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 Github repository * Enable Github Actions checks and steps for a new repository. * Find a Github Action to lint and check a Dockerfile to prevent issues before merging on pull requests. * Add Github Secrets and reuse them in a Github Action * Validate that a container builds correctly, and automatically push to dockerhub
MLOps workflow with Github Actions by Alfredo Deza( Visual )

2 editions published in 2021 in English and held by 123 WorldCat member libraries worldwide

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 and the ONNX runtime * Package the model and verify it works locally * Setup a Github Action to authenticate to Azure ML and download a previously registered model * Build the new container as a Github Action, authenticate to Docker Hub or Github Packages * Push the new container to the Github registry or any other registry like Docker Hub
Distributed Jenkins builds with containers by Alfredo Deza( Visual )

2 editions published in 2021 in English and held by 123 WorldCat member libraries worldwide

Distribute the load of Jenkins builds with a remote Docker instance or Kubernetes server in this 1-hour long tutorial Topics include: * Configure a remote Docker instance to interact with the master Jenkins server * Modify an existing job to use Docker to do builds using labels * Setup a remote kubernetes instance to connect to Jenkins with JNLP * Use the right container image to connect back to Jenkins as a remote container node
AWS Certified DevOps Engineer - Professional by Noah Gift( Visual )

2 editions published in 2020 in English and held by 122 WorldCat member libraries worldwide

Nearly 4 Hours of Video Instruction Cloud adoption is greater than ever. However, there is a shortage of skilled practitioners who not only can use the cloud, but can optimize it. DevOps is a catchall word for a series of behaviors that can dramatically increase the operational efficiency of the cloud. DevOps best practices include continuous integration, continuous delivery, Microservices, teamwork and collaboration, and monitoring. This course covers the essentials of DevOps Professional on AWS and prepares a candidate to sit for the DevOps Professional Certification exam. Description The AWS Certified Developer Complete Video Course focuses on the AWS Certified DevOps Engineer - Professional Exam. The leader in cloud computing by market share, Amazon and their DevOps Professional certification allows you to demonstrate that you have mastered the essential skills of operationalizing a cloud. Seven main categories are covered: AWS Certified DevOps Engineer Overview; SDLC Automation; Configuration Management and Infrastructure as Code; Monitoring and Logging; Policies and Standards Automation; Incident and Event Response; and High Availability, Fault Tolerance, and Disaster Recovery. The material focuses on teaching the concepts necessary to pass the exam and be competent as a DevOps practitioner on AWS. About the Instructor Noah Gift is a lecturer at UC Davis Graduate School of Management MSBA program, the Graduate Data Science program, MSDS, at Northwestern, the Data Science program at UC Berkeley, and the USF Health Informatics program. He is teaching and designing graduate Machine Learning, AI, Data Science courses, and consulting on Machine Learning and Cloud Architecture for students and faculty. These responsibilities include leading a multi-cloud certification initiative for students. Noah has published nearly 100 technical publications, including books on subjects ranging from Cloud Machine Learning to DevOps. He has published more than100 technical publications, including three books on subjects ranging from Cloud Machine Learning to DevOps. Gift received an MBA from UC Davis, a M.S. in Computer Information Systems from Cal State Los Angeles, and a B.S. in Nutritional Science from Cal Poly San Luis Obispo. Currently, he consults startups and other companies on Machine Learning, Cloud Architecture and CTO-level consulting as the founder of Pragmatic AI Labs. His most recent book is Pragmatic AI: An Introduction to Cloud-Base
AWS Certified Machine Learning-Specialty (ML-S) by Noah Gift( Visual )

2 editions published in 2019 in English and held by 122 WorldCat member libraries worldwide

More Than 7 Hours of Video Instruction Overview This course covers the essentials of Machine Learning on AWS and prepares a candidate to sit for the AWS Machine Learning-Specialty (ML-S) Certification exam. Four main categories are covered: Data Engineering, EDA (Exploratory Data Analysis), Modeling, and Operations. Description This 7+ hour Complete Video Course is fully geared toward the AWS Machine Learning-Specialty (ML-S) Certification exam. The course offers a modular lesson and sublesson approach, with a mix of screencasting and headhsot treatment. Data Engineering instruction covers the ingestion, cleaning, and maintenance of data on AWS. Exploratory Data Analysis covers topics including data visualization, descriptive statistics, and dimension reduction and includes information on relevant AWS services. Machine Learning Modeling covers topics including feature engineering, performance metrics, overfitting, and algorithm selection. Operations covers deploying models, A/B testing, using AI services versus training your own model, and proper cost utilization. The supporting code for this LiveLesson is located at http://www.informit.com/store/aws-certified-machine-learning-specialty-ml-s-complete-9780135556511 . About the Instructor Noah Gift is a lecturer and consultant at both the UC Davis Graduate School of Management MSBA program and the Graduate Data Science program, MSDS, at Northwestern. He teaches and designs graduate machine learning, AI, data science courses, and consulting on machine learning and cloud architecture for students and faculty. These responsibilities include leading a multi-cloud certification initiative for students. Noah is a Python Software Foundation Fellow, AWS Subject Matter Expert (SME) on Machine Learning, AWS Certified Solutions Architect, AWS Academy accredited instructor, Google Certified Professional Cloud Architect, and Microsoft MTA on Python. Noah has published close to 100 technical publications including two books on subjects ranging from cloud machine learning to DevOps. Noah received an MBA from UC Davis, a M.S. in Computer Information Systems from Cal State Los Angeles, and a B.S. in Nutritional Science from Cal Poly San Luis Obispo. Currently he consults for startups and other companies on machine learning, cloud architecture, and CTO-level consulting as the founder of Pragmatic AI Labs. His most recent publications are Pragmatic AI: An introduction to Cloud-Based Machine Learning (Pear
Scraping Websites with Python by Alfredo Deza( Visual )

3 editions published in 2021 in English and held by 121 WorldCat member libraries worldwide

Sometimes scraping is the only way to extract meaningful data when there are no options like an accessible API. Parsing raw HTML can be intimidating and full of failures if you aren't used to existing tooling that can help you parse faster and more efficiently. In this video, learn all the basics including some advanced techniques to parse HTML and extract data with the Scrapy library in Python. k Topics include: * Install, configure, and create a new project with Scrapy, a powerful scraping library written in Python * See what is required to start parsing a website, including looking at raw HTML, tags, and CSS. * Identify data to create a dataset or datasets to perform data science analysis later * Capture parsed data and save it in different formats locally * Ultra fast scraping techniques by using the filesystem directly A few resources that are helpful if you are trying to do scraping, some of them covered in the course: * Scrapy Library * Scrapy Getting started tutorial
AutoML with Apple CreateML by Alfredo Deza( Visual )

2 editions published in 2021 in English and held by 121 WorldCat member libraries worldwide

Learn to build Machine Learning solutions without writing any code with CreateML from Apple. Topics include: * Computer Vision * Image Classification * OS X * Apple * Core ML
Google VS Apple AutoML Computer Vision by Alfredo Deza( Visual )

2 editions published in 2021 in English and held by 121 WorldCat member libraries worldwide

Learn to use Google AutoML to build a computer vision prediction model via their Qwiklabs website. Later, compare Apple's CreateML with the same data set and build an AutoML prediction model that deploy to the edge. Topics include: * Google AutoML * Apple CreateML * Apple CoreML * Computer Vision * Cloud Computing * Single label image classification * Using AutoML as a prototyping Tool * Edge Computer Vision Models
Introduction to Software Bill of Materials by Alfredo Deza( Visual )

2 editions published in 2021 in English and held by 121 WorldCat member libraries worldwide

What is an SBOM (Software Bill Of Materials) and why should you care? An SBOM is a critical cybersecurity component to keep track and catalog what is installed (and at what versions) in production environments. With recent cybersecurity threats, SBOMs play an important role to implement a remediation strategy when threats and vulnerabilities are reported. Without an SBOM, it is borderline impossible to detect what exactly is released into production, and what may be vulnerable today. Topics include: * Understand the concepts behind an SBOM * Create an SBOM and use different output formats like CycloneDX to import into other systems * Use an SBOM to detect CVE and other vulnerabilities associated with installed software * Capture information about pre-installed system dependencies and nested dependencies * Use CycloneDX and other machine-readable formats like JSON to import outputs into other systems A few resources that are helpful if you are trying to get started with SBOMs, generating them and using them to capture vulnerabilities: * A simple, user-friendly SBOM generator: Syft * A fast vulnerability matcher that uses SBOMs as input: Grype * The CycloneDX format
AWS Certified Big Data : specialty complete video course and practice test video training by Robert Jordan( Visual )

1 edition published in 2019 in English and held by 121 WorldCat member libraries worldwide

"AWS leads the world in cloud computing and big data. This course offers the complete package to help practitioners master the core skills and competencies needed to build successful, high-value big data applications, with a clear path toward passing the certification exam AWS Certified Big Data - Specialty. This course provides a solid foundation in all areas required to pass the AWS Certified Big Data Specialty Exam, including Collection, Storage, Processing, Analysis, Visualization, and Data Security. In addition, multiple quizzes and a practice exam prepare the student for the formal Certification Exam administered by AWS."--Resource description page
 
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Python for Unix and Linux system administration
Covers
Pragmatic AI : an introduction to cloud-based machine learning
Alternative Names
Gift

기프트, 노아

Languages
English (81)