5/3/2017 - New York
Event: http://testleadershipcongress-ny.com/machine-learning-society.html
N.B. Sources are linked in the slides.
Get Sam Putnam's essays and talk schedule in your inbox: https://upscri.be/2611dd/
ATAGTR2017 Artificial Intelligence in Software Testing – DemystifiedAgile Testing Alliance
The presentation on Artificial Intelligence in Software Testing – Demystified was done during #ATAGTR2017, one of the largest global testing conference. All copyright belongs to the author.
Author and presenter : Ramakrishnan Venkatasubramanian
Automated testing of software applications using machine learning editedMilind Kelkar
Machine Learning is the next internet. It is the backbone of search engines, driverless car, paperless banking, and facial recognition in forensics. Running automated software tests with lesser human intervention without the risk of schedule delays is now a reality. This presentation will explore several practical machine learning concepts that are being adopted to test software applications.
Artificial intelligence (AI) is the most important technology for software testers to understand today. All software will soon have AI-powered components, and they are unlike anything you’ve ever tested before. As risky as AI can be, it is a powerful weapon for testers to solve some of their most painful testing challenges today. The web was great, mobile is interesting, but AI will truly change the way you build and test all software. Jason Arbon gives a brief introduction to AI and machine learning (ML) so you can nod your head knowingly when the topics come up. Explore how products that leverage machine learning are tested at Google, Microsoft, and new startups. Learn the basics of labeling data, training sets, testing sets, measuring quality, and the risks of retraining neural networks. Even learn how to apply AI and ML to your own testing work today. Join Jason to get a glimpse into the new world where we will work hand-in-hand with our new AI bot friends. Don’t miss the AI train—it will change everything.
The landscape for software testing has never been so broad. Applications today interact with other applications through APIs. And in return they leverage legacy systems, while they grow in complexity from one day to the next in a nonlinear fashion. So what does that mean for analysts, developers, and testers?
The 2016-17 World Quality Report suggests that AI will help. “We believe that the most important solution to overcome increasing QA and Testing Challenges will be the emerging introduction of machine-based intelligence,” the report states.
We have witnessed the mobile and computer revolution — now similarly — artificial intelligence (AI) is revealing its potential; not only by the way we live, but also within the majority of industries,. And software testing is no exception.
Facebook and Google aren’t the only companies applying AI techniques. In this session, we will explore how software testers can leverage AI and how tools may need to evolve. For instance, Helix ALM accelerates the development-to-release process, catches bugs earlier, and supports the transition to new development techniques.
In this webinar, we will also discuss three key elements that will significantly change software development with the evolution of “Artificial Intelligence”.
Bringing Quality Design Systems to Life with Storybook & ApplitoolsApplitools
** Full webinar recording: https://youtu.be/R6WnEzlMHac **
Bringing design systems and component libraries to life can be a large, challenging process without the right tools. On top of that, maintaining a high level of quality throughout those systems brings its own challenge.
While there’s no shortage of ways to manually create a design system from scratch, doing so can be time consuming and can lead to technical debt when the system itself isn’t itself in a structure.
Storybook is a tool for developers that helps bring design systems and component libraries to life, providing structured tooling and a web dashboard. It gives those developers, and even designers, a way to focus on each individual component while being able to see the system from a higher perspective.
On top of that, Applitools is an automated Visual Testing solution that easily stacks right on top of Storybook with the Storybook Eyes SDK. With a single command, Applitools provides full test coverage for each component of your design system.
Join Developer Advocate, Colby Fayock, as he walks through:
How to take advantage of using Storybook to build scalable design systems
How Applitools makes automating the testing of those components easy
How to focus on building great experiences while automating quality checks with visual testing
Curious to know what 3,400 software developers and QA experts think about the current and future state of the software testing industry?
Whether you’re a developer, QA engineer, manager, or any other role working in the software industry, SmartBear’s 2017 State of Testing Survey Report will provide you an exciting deep-dive look into industry trends in software testing, team dynamics, development models, and outlooks on the future of software testing.
This document provides an introduction to software testing. It explains that testing is the process of finding errors in a program. Testing is important to find failures before public release, as failures can have major consequences. While developers can test, an independent test engineer is needed for objectivity. Testing requires thinking ahead to break code, and is more creative than development. The document contrasts manual and automated testing, noting automation's advantages in speed, repeatability, and reliability. It then describes CegoSoft's software testing training program, labs, tools, placements, and project types.
ATAGTR2017 Artificial Intelligence in Software Testing – DemystifiedAgile Testing Alliance
The presentation on Artificial Intelligence in Software Testing – Demystified was done during #ATAGTR2017, one of the largest global testing conference. All copyright belongs to the author.
Author and presenter : Ramakrishnan Venkatasubramanian
Automated testing of software applications using machine learning editedMilind Kelkar
Machine Learning is the next internet. It is the backbone of search engines, driverless car, paperless banking, and facial recognition in forensics. Running automated software tests with lesser human intervention without the risk of schedule delays is now a reality. This presentation will explore several practical machine learning concepts that are being adopted to test software applications.
Artificial intelligence (AI) is the most important technology for software testers to understand today. All software will soon have AI-powered components, and they are unlike anything you’ve ever tested before. As risky as AI can be, it is a powerful weapon for testers to solve some of their most painful testing challenges today. The web was great, mobile is interesting, but AI will truly change the way you build and test all software. Jason Arbon gives a brief introduction to AI and machine learning (ML) so you can nod your head knowingly when the topics come up. Explore how products that leverage machine learning are tested at Google, Microsoft, and new startups. Learn the basics of labeling data, training sets, testing sets, measuring quality, and the risks of retraining neural networks. Even learn how to apply AI and ML to your own testing work today. Join Jason to get a glimpse into the new world where we will work hand-in-hand with our new AI bot friends. Don’t miss the AI train—it will change everything.
The landscape for software testing has never been so broad. Applications today interact with other applications through APIs. And in return they leverage legacy systems, while they grow in complexity from one day to the next in a nonlinear fashion. So what does that mean for analysts, developers, and testers?
The 2016-17 World Quality Report suggests that AI will help. “We believe that the most important solution to overcome increasing QA and Testing Challenges will be the emerging introduction of machine-based intelligence,” the report states.
We have witnessed the mobile and computer revolution — now similarly — artificial intelligence (AI) is revealing its potential; not only by the way we live, but also within the majority of industries,. And software testing is no exception.
Facebook and Google aren’t the only companies applying AI techniques. In this session, we will explore how software testers can leverage AI and how tools may need to evolve. For instance, Helix ALM accelerates the development-to-release process, catches bugs earlier, and supports the transition to new development techniques.
In this webinar, we will also discuss three key elements that will significantly change software development with the evolution of “Artificial Intelligence”.
Bringing Quality Design Systems to Life with Storybook & ApplitoolsApplitools
** Full webinar recording: https://youtu.be/R6WnEzlMHac **
Bringing design systems and component libraries to life can be a large, challenging process without the right tools. On top of that, maintaining a high level of quality throughout those systems brings its own challenge.
While there’s no shortage of ways to manually create a design system from scratch, doing so can be time consuming and can lead to technical debt when the system itself isn’t itself in a structure.
Storybook is a tool for developers that helps bring design systems and component libraries to life, providing structured tooling and a web dashboard. It gives those developers, and even designers, a way to focus on each individual component while being able to see the system from a higher perspective.
On top of that, Applitools is an automated Visual Testing solution that easily stacks right on top of Storybook with the Storybook Eyes SDK. With a single command, Applitools provides full test coverage for each component of your design system.
Join Developer Advocate, Colby Fayock, as he walks through:
How to take advantage of using Storybook to build scalable design systems
How Applitools makes automating the testing of those components easy
How to focus on building great experiences while automating quality checks with visual testing
Curious to know what 3,400 software developers and QA experts think about the current and future state of the software testing industry?
Whether you’re a developer, QA engineer, manager, or any other role working in the software industry, SmartBear’s 2017 State of Testing Survey Report will provide you an exciting deep-dive look into industry trends in software testing, team dynamics, development models, and outlooks on the future of software testing.
This document provides an introduction to software testing. It explains that testing is the process of finding errors in a program. Testing is important to find failures before public release, as failures can have major consequences. While developers can test, an independent test engineer is needed for objectivity. Testing requires thinking ahead to break code, and is more creative than development. The document contrasts manual and automated testing, noting automation's advantages in speed, repeatability, and reliability. It then describes CegoSoft's software testing training program, labs, tools, placements, and project types.
[webinar] Best of Breed: Successful Test Automation Practices from Innovative...Applitools
While test automation is a struggle for most teams everywhere, there are companies who have mastered their technique and are executing a very successful test automation strategy.
In this talk, Angie Jones shares the research on how top companies and global brands are approaching test automation, and successfully implementing it.
Angie was joined by a panel of QA executives, who also shared what they are seeing in the industry in regards to successful (and not so successful) test automation practices:
* Theresa Neate - QA Practise Lead @ Real Estate Group
* Amrit Sadhab - Digital Practise Lead @ Origin Energy
* Karen Mangio - QA Practise Lead @ NAB Mobile
* Cameron Bradley - Head of QA @ Tabcorp
ATAGTR2017 Cost-effective Security Testing Approaches for Web, Mobile & Enter...Agile Testing Alliance
The presentation on Cost-effective Security Testing Approaches for Web, Mobile & Enterprise Application was done during #ATAGTR2017, one of the largest global testing conference. All copyright belongs to the author.
Author and presenter : Varadarajan V. G.
What is Shift Left Testing? Do you need to use that term to improve your Software Testing and Development process? I don't think so.
- why I don't use the term Shift Left
- Explanation of what Shift Left means when people use it
- Explanation of what Shift Left might mean when people hear it
- How to Shift Left incorrectly
- How to improve your test process without using the phrase Shift Left.
Hire me for consultancy and buy my online books and training at:
- https://compendiumdev.co.uk
- http://eviltester.com
- http://seleniumsimplified.com
- http://javafortesters.com
The Whole Team Approach to Quality in Continuous Deliverylisacrispin
Lisa shares her teams' experiences with making a team commitment to quality and learning ways to build it in and fit all testing activities into continuous delivery.
Shift left testing involves moving testing as far left or as early in the development process as possible to find and prevent defects early. This is opposed to traditional testing, which only occurred right before release. Shift left testing improves quality by identifying issues early when they are cheaper to fix. While shift left is often best, shift right testing post-production may also be useful in some cases to enhance customer experience and ensure proper test coverage and automation. To shift left, organizations can engage stakeholders early, do static testing of requirements and design, and see benefits like increased automation, delivery speed, and satisfaction.
Testing Design System Changes Across Your Application -- Intuit Use Case -- w...Applitools
This document discusses Intuit's use of design systems and testing methods. It provides context on Intuit as a company and the speaker's role. It defines what design systems are and how they are used at Intuit for products like TurboTax to maintain design consistency at scale. The document outlines the goals of testing design systems broadly across functionality, visuals, performance, accessibility, and more. It walks through Intuit's workflow and tools for testing design system changes, including unit/integration tests, accessibility checks, performance tests, visual regression testing, and testing components and full page mocks. Additional bonus tools used in Intuit's testing setup are also mentioned.
Enterprise Ready Test Execution Platform for Mobile AppsVijayan Srinivasan
When it comes to Mobile test execution, appium framework is the default choice of engineers for writing test cases. Running the appium testcases against multiple Android versions in parallel can be achieved via another open source tool called selenium grid.
Unfortunately selenium grid is not enterprise ready. Meaning the selenium grid cannot be used as a single test execution platform across enterprise level companies due to following issues
• Not available as a Web Application to run from Intuit Standard Containers (Tomcat, WHP)
• Device registry is maintained in-memory
• No support for High Availability / Disaster Recovery
• No support for External Device Cloud
• Not much debugging support (Screenshot, Exception or Log messages)
This talk will be covering the limitations of selenium grid and how Intuit modified the selenium grid to suit for enterprise needs.
Testing Hourglass at Jira Frontend - by Alexey Shpakov, Sr. Developer @ Atlas...Applitools
Alexey Shpakov presents on testing in Jira Frontend. He discusses the testing pyramid with unit, integration, and end-to-end tests. He then introduces the concept of a "testing hourglass" which adds deployment and post-deployment verification to the pyramid. Key aspects of each type of test are discussed such as using feature flags, monitoring for flaky tests, and gradual rollouts to reduce risk.
Get testing bottlenecks out of your pipelineslisacrispin
When teams move towards continuous delivery and deployment, how do they manage the manual stages in their deployment pipeline? This talk gives some techniques to visualize pipelines, identify bottlenecks, find ways to remove them.
The presentation on Wearable App Testing was done during #ATAGTR2017, one of the largest global testing conference. All copyright belongs to the author.
Author and presenter : Himansha Tyagi
By applying linting (static code analysis) tools to test code, preferably the same tools as for application code, tests can be improved which can eventually lead to better maintainability, readability and more robust tests, without even running them!
Diving into the World of Test Automation The Approach and the TechnologiesQASymphony
This presentation was originally given at Quality Jam London. Elise covered test automation and the progression for test automation that you might encounter. The session agenda included:
The stages of the test team
Why are we automating?
What are we automating?
How are we automating?
What languages should we use?
What frameworks and libraries should we use?
Open source or proprietary?
Learn more at www.qualityjam.com
[TAQfull Meetup] Angie Jones + Expert Panel: Best Practices in Quality Manage...Applitools
** Meetup session recording: https://youtu.be/Vo-PhgrOT0A **
While test automation is a struggle for most teams across the globe, there are companies who have mastered this -- and are executing a very successful test automation strategy.
In this special 90-minute live session, industry thought-leader Angie Jones shares the research on how top brands & global companies are approaching test automation, how they are successfully implementing it, and what are their building blocks for their top-notch quality teams.
Angie was joined by Quality Engineering executives, who shared what they are seeing in the industry in regards to successful (and not so successful) test automation practices:
* Stuart Day - Principal QA - Digital @ Dunelm and co-founder/ organizer @ TAQfull Meet-Up
* Marie Drake - Principle Test Automation Engineer @ NewsUK / Cypress.io Ambassador
* Matt Lowry - Principle Test Engineer @ BP (via ECS)
Testing Solutions for Hyper Connected Apps by Sivakumar AnnaQA or the Highway
This document discusses testing solutions for apps that utilize various device interfaces and peripherals. It outlines challenges in testing location services, cameras, Bluetooth, biometrics and other device features. It then presents a simulator-based solution called a Digital App Automation Library that allows automating tests for these device interfaces through a portal. Several demo use cases are described that showcase how the library can be used to simulate location services and camera image injection for testing utility maintenance mobile apps.
Myth vs Reality: Understanding AI/ML for QA Automation - w/ Jonathan LippsApplitools
** Full webinar recording -- https://youtu.be/ihpAsmRtGuM **
Artificial Intelligence and Machine Learning (AI/ML) have seen application in a variety of fields, including the automation of QA tasks. But what are they exactly? What distinguishes different instances and applications of AI, for example? What are the horizons of these technologies in the field of QA?
The promise of AI/ML must be understood correctly to be harnessed appropriately. As with any buzzword, many technologies and products are offered under the guise of AI/ML without satisfying the definition. The industry is reforming itself around the promise that AI/ML holds often without a clear understanding of the technical limitations that give the promise its boundaries.
In this webinar, test automation guru Jonathan Lipps gives a detailed overview of the concepts that underpin AI/ML, and discuss their ramifications for the work of QA automation.
In addition to a discussion of AI/ML in general, Jonathan looks at examples from the QA industry. These examples will help give attendees the basic understanding required to cut through the marketing language. so we can clearly evaluate AI/ML solutions, and calibrate expectations about the benefit of AI/ML in QA, both as it stands today and in the future.
Build Your Mobile App Quality and Test StrategyTechWell
Let’s build a mobile app quality and testing strategy together. Whether you have a web, hybrid, or native app, building a quality and testing strategy means (1) knowing what data and tools you have available to make agile decisions, (2) understanding your customers and your competitors, and (3) testing your app under real-world conditions. Jason Arbon guides you through the latest techniques, data, and tools to ensure the awesomeness of your mobile app quality and testing strategy. Leave this interactive session with a strategy for your very own app—or one you pretend to own. The information Jason shares is based on data from Appdiff’s next-gen mobile app testing platform, lessons from Applause/uTest’s crowd, text mining hundreds of millions of app store reviews, and in-depth discussions with top mobile app development teams.
Leveraging AI and ML in Test Management Systems - DevOps NextPerfecto by Perforce
AI and ML can be utilized to improve test management and quality, and the impact of changes from design into production. Learn about the various stages of software development life cycle from planning and design, through coding and testing, and shows how AI and ML can benefit these stages from within a test management system.
Visual Validation - The Missing Tip of the Automation PyramidAnand Bagmar
The Test Automation Pyramid is not a new concept. The top of the pyramid is our UI / end-2-end functional tests - which should cover the breadth of the product.
What the functional tests cannot capture though, is the aspects of UX validations that can only be seen and in some cases, captured by the human eye. This is where the new buzzwords of AI & ML can truly help.
In this session, we will explore why Visual Validation is an important cog in the wheel of Test Automation and also different tools and techniques that can help achieve this. We will also see a demo of Applitools Eyes - and how it can be a good option to close this gap in automation!
This is a presentation given to the DC Agile Software Testing (D-CAST) meetup group that discusses real-world testing challenges. The meetup also included a live demo of SpiraTest and Rapise tools that were used to demonstrate the concepts.
"Software Quality in the Service of Innovation in the Insurance Industry"Applitools
This document discusses software quality in the insurance industry. It introduces Joe Emison, CTO of Branch Insurance, and discusses how Branch builds software frequently in small increments using test automation. It notes challenges with traditional test automation approaches and outlines Branch's approach using unit tests, API tests, and data-driven end-to-end tests run continuously. The document also discusses how ProdPerfect and Applitools can work together to provide effortless functional and visual testing through data analysis, test case discovery, and visual AI.
Artifical Intelligence and Machine Learning 201, AWS Federal Pop-Up LoftAmazon Web Services
Come join us for a one-day session where you will learn about the science of computer vision (CV) and train custom CV models utilizing Amazon SageMaker. In this course, you'll learn about Amazon's managed machine learning platform and utilize publicly available real-world ground truth data sets to train models leveraging the built-in ML algorithms of Amazon SageMaker to detect objects and buildings. This is a hands-on workshop, attendees should bring your own laptops.
[webinar] Best of Breed: Successful Test Automation Practices from Innovative...Applitools
While test automation is a struggle for most teams everywhere, there are companies who have mastered their technique and are executing a very successful test automation strategy.
In this talk, Angie Jones shares the research on how top companies and global brands are approaching test automation, and successfully implementing it.
Angie was joined by a panel of QA executives, who also shared what they are seeing in the industry in regards to successful (and not so successful) test automation practices:
* Theresa Neate - QA Practise Lead @ Real Estate Group
* Amrit Sadhab - Digital Practise Lead @ Origin Energy
* Karen Mangio - QA Practise Lead @ NAB Mobile
* Cameron Bradley - Head of QA @ Tabcorp
ATAGTR2017 Cost-effective Security Testing Approaches for Web, Mobile & Enter...Agile Testing Alliance
The presentation on Cost-effective Security Testing Approaches for Web, Mobile & Enterprise Application was done during #ATAGTR2017, one of the largest global testing conference. All copyright belongs to the author.
Author and presenter : Varadarajan V. G.
What is Shift Left Testing? Do you need to use that term to improve your Software Testing and Development process? I don't think so.
- why I don't use the term Shift Left
- Explanation of what Shift Left means when people use it
- Explanation of what Shift Left might mean when people hear it
- How to Shift Left incorrectly
- How to improve your test process without using the phrase Shift Left.
Hire me for consultancy and buy my online books and training at:
- https://compendiumdev.co.uk
- http://eviltester.com
- http://seleniumsimplified.com
- http://javafortesters.com
The Whole Team Approach to Quality in Continuous Deliverylisacrispin
Lisa shares her teams' experiences with making a team commitment to quality and learning ways to build it in and fit all testing activities into continuous delivery.
Shift left testing involves moving testing as far left or as early in the development process as possible to find and prevent defects early. This is opposed to traditional testing, which only occurred right before release. Shift left testing improves quality by identifying issues early when they are cheaper to fix. While shift left is often best, shift right testing post-production may also be useful in some cases to enhance customer experience and ensure proper test coverage and automation. To shift left, organizations can engage stakeholders early, do static testing of requirements and design, and see benefits like increased automation, delivery speed, and satisfaction.
Testing Design System Changes Across Your Application -- Intuit Use Case -- w...Applitools
This document discusses Intuit's use of design systems and testing methods. It provides context on Intuit as a company and the speaker's role. It defines what design systems are and how they are used at Intuit for products like TurboTax to maintain design consistency at scale. The document outlines the goals of testing design systems broadly across functionality, visuals, performance, accessibility, and more. It walks through Intuit's workflow and tools for testing design system changes, including unit/integration tests, accessibility checks, performance tests, visual regression testing, and testing components and full page mocks. Additional bonus tools used in Intuit's testing setup are also mentioned.
Enterprise Ready Test Execution Platform for Mobile AppsVijayan Srinivasan
When it comes to Mobile test execution, appium framework is the default choice of engineers for writing test cases. Running the appium testcases against multiple Android versions in parallel can be achieved via another open source tool called selenium grid.
Unfortunately selenium grid is not enterprise ready. Meaning the selenium grid cannot be used as a single test execution platform across enterprise level companies due to following issues
• Not available as a Web Application to run from Intuit Standard Containers (Tomcat, WHP)
• Device registry is maintained in-memory
• No support for High Availability / Disaster Recovery
• No support for External Device Cloud
• Not much debugging support (Screenshot, Exception or Log messages)
This talk will be covering the limitations of selenium grid and how Intuit modified the selenium grid to suit for enterprise needs.
Testing Hourglass at Jira Frontend - by Alexey Shpakov, Sr. Developer @ Atlas...Applitools
Alexey Shpakov presents on testing in Jira Frontend. He discusses the testing pyramid with unit, integration, and end-to-end tests. He then introduces the concept of a "testing hourglass" which adds deployment and post-deployment verification to the pyramid. Key aspects of each type of test are discussed such as using feature flags, monitoring for flaky tests, and gradual rollouts to reduce risk.
Get testing bottlenecks out of your pipelineslisacrispin
When teams move towards continuous delivery and deployment, how do they manage the manual stages in their deployment pipeline? This talk gives some techniques to visualize pipelines, identify bottlenecks, find ways to remove them.
The presentation on Wearable App Testing was done during #ATAGTR2017, one of the largest global testing conference. All copyright belongs to the author.
Author and presenter : Himansha Tyagi
By applying linting (static code analysis) tools to test code, preferably the same tools as for application code, tests can be improved which can eventually lead to better maintainability, readability and more robust tests, without even running them!
Diving into the World of Test Automation The Approach and the TechnologiesQASymphony
This presentation was originally given at Quality Jam London. Elise covered test automation and the progression for test automation that you might encounter. The session agenda included:
The stages of the test team
Why are we automating?
What are we automating?
How are we automating?
What languages should we use?
What frameworks and libraries should we use?
Open source or proprietary?
Learn more at www.qualityjam.com
[TAQfull Meetup] Angie Jones + Expert Panel: Best Practices in Quality Manage...Applitools
** Meetup session recording: https://youtu.be/Vo-PhgrOT0A **
While test automation is a struggle for most teams across the globe, there are companies who have mastered this -- and are executing a very successful test automation strategy.
In this special 90-minute live session, industry thought-leader Angie Jones shares the research on how top brands & global companies are approaching test automation, how they are successfully implementing it, and what are their building blocks for their top-notch quality teams.
Angie was joined by Quality Engineering executives, who shared what they are seeing in the industry in regards to successful (and not so successful) test automation practices:
* Stuart Day - Principal QA - Digital @ Dunelm and co-founder/ organizer @ TAQfull Meet-Up
* Marie Drake - Principle Test Automation Engineer @ NewsUK / Cypress.io Ambassador
* Matt Lowry - Principle Test Engineer @ BP (via ECS)
Testing Solutions for Hyper Connected Apps by Sivakumar AnnaQA or the Highway
This document discusses testing solutions for apps that utilize various device interfaces and peripherals. It outlines challenges in testing location services, cameras, Bluetooth, biometrics and other device features. It then presents a simulator-based solution called a Digital App Automation Library that allows automating tests for these device interfaces through a portal. Several demo use cases are described that showcase how the library can be used to simulate location services and camera image injection for testing utility maintenance mobile apps.
Myth vs Reality: Understanding AI/ML for QA Automation - w/ Jonathan LippsApplitools
** Full webinar recording -- https://youtu.be/ihpAsmRtGuM **
Artificial Intelligence and Machine Learning (AI/ML) have seen application in a variety of fields, including the automation of QA tasks. But what are they exactly? What distinguishes different instances and applications of AI, for example? What are the horizons of these technologies in the field of QA?
The promise of AI/ML must be understood correctly to be harnessed appropriately. As with any buzzword, many technologies and products are offered under the guise of AI/ML without satisfying the definition. The industry is reforming itself around the promise that AI/ML holds often without a clear understanding of the technical limitations that give the promise its boundaries.
In this webinar, test automation guru Jonathan Lipps gives a detailed overview of the concepts that underpin AI/ML, and discuss their ramifications for the work of QA automation.
In addition to a discussion of AI/ML in general, Jonathan looks at examples from the QA industry. These examples will help give attendees the basic understanding required to cut through the marketing language. so we can clearly evaluate AI/ML solutions, and calibrate expectations about the benefit of AI/ML in QA, both as it stands today and in the future.
Build Your Mobile App Quality and Test StrategyTechWell
Let’s build a mobile app quality and testing strategy together. Whether you have a web, hybrid, or native app, building a quality and testing strategy means (1) knowing what data and tools you have available to make agile decisions, (2) understanding your customers and your competitors, and (3) testing your app under real-world conditions. Jason Arbon guides you through the latest techniques, data, and tools to ensure the awesomeness of your mobile app quality and testing strategy. Leave this interactive session with a strategy for your very own app—or one you pretend to own. The information Jason shares is based on data from Appdiff’s next-gen mobile app testing platform, lessons from Applause/uTest’s crowd, text mining hundreds of millions of app store reviews, and in-depth discussions with top mobile app development teams.
Leveraging AI and ML in Test Management Systems - DevOps NextPerfecto by Perforce
AI and ML can be utilized to improve test management and quality, and the impact of changes from design into production. Learn about the various stages of software development life cycle from planning and design, through coding and testing, and shows how AI and ML can benefit these stages from within a test management system.
Visual Validation - The Missing Tip of the Automation PyramidAnand Bagmar
The Test Automation Pyramid is not a new concept. The top of the pyramid is our UI / end-2-end functional tests - which should cover the breadth of the product.
What the functional tests cannot capture though, is the aspects of UX validations that can only be seen and in some cases, captured by the human eye. This is where the new buzzwords of AI & ML can truly help.
In this session, we will explore why Visual Validation is an important cog in the wheel of Test Automation and also different tools and techniques that can help achieve this. We will also see a demo of Applitools Eyes - and how it can be a good option to close this gap in automation!
This is a presentation given to the DC Agile Software Testing (D-CAST) meetup group that discusses real-world testing challenges. The meetup also included a live demo of SpiraTest and Rapise tools that were used to demonstrate the concepts.
"Software Quality in the Service of Innovation in the Insurance Industry"Applitools
This document discusses software quality in the insurance industry. It introduces Joe Emison, CTO of Branch Insurance, and discusses how Branch builds software frequently in small increments using test automation. It notes challenges with traditional test automation approaches and outlines Branch's approach using unit tests, API tests, and data-driven end-to-end tests run continuously. The document also discusses how ProdPerfect and Applitools can work together to provide effortless functional and visual testing through data analysis, test case discovery, and visual AI.
Artifical Intelligence and Machine Learning 201, AWS Federal Pop-Up LoftAmazon Web Services
Come join us for a one-day session where you will learn about the science of computer vision (CV) and train custom CV models utilizing Amazon SageMaker. In this course, you'll learn about Amazon's managed machine learning platform and utilize publicly available real-world ground truth data sets to train models leveraging the built-in ML algorithms of Amazon SageMaker to detect objects and buildings. This is a hands-on workshop, attendees should bring your own laptops.
Amazon SageMaker - ML for every developer & data scientist ft. Workday - AIM2...Amazon Web Services
The document discusses Amazon SageMaker, AWS's platform for building, training, and deploying machine learning models at scale. It highlights key SageMaker capabilities like pre-built notebooks, built-in algorithms, one-click training on high-performance infrastructure, model optimization, and one-click deployment. It also discusses other AWS machine learning services like Ground Truth for data labeling, AWS Marketplace for accessing algorithms and models, and SageMaker Neo for optimized model deployment.
#ATAGTR2019 Presentation "Assuring Quality for AI based applications" By Vino...Agile Testing Alliance
Vinod Sundararaju Antony who is Director at Cognizant Technology Solutions along with Senthilkumar Thirumalaisamy who is a Manager Automation Architect at Cognizant Technology Solutions and Santhosh Kumar Vasudevan who is a Lead System Architect at Cognizant Technology Solutions took a Session on "Assuring Quality for AI based applications" at Global Testing Retreat #ATAGTR2019
Please refer our following post for session details:
https://atablogs.agiletestingalliance.org/2019/12/04/global-testing-retreat-atagtr2019-welcomes-vinod-antony-sundaraju-as-our-esteemed-speaker/
https://atablogs.agiletestingalliance.org/2019/12/04/global-testing-retreat-atagtr2019-welcomes-senthilkumar-thirumalaisamy-as-our-esteemed-speaker/
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EA Algorithm in Machine Learning | EdurekaEdureka!
YouTube Link: https://youtu.be/DIADjJXrgps
** Machine Learning Certification Training: https://www.edureka.co/machine-learning-certification-training **
This Edureka PPT on 'EM Algorithm In Machine Learning' covers the EM algorithm along with the problem of latent variables in maximum likelihood and Gaussian mixture model.
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Quality and Testing of AI Algorithms - Enterprise Deep Learning
1. Quality and Testing of
Artificial Intelligence
Algorithms
5/3/2017
Sam Putnam, Enterprise Deep Learning, LLC
www.EnterpriseDeepLearning.com
Want to learn more?
I am teaching the Deploying Deep
Learning Track at Deep Learning Conf®
Tickets are available now:
www.DeepLearningConf.com
2. Topics
Machine Learning Algorithms in Production
Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Spam Classification
Activity - Introductions
Recommendation Systems
Neural Networks
Decision Tree Classifiers
5/3/2017
3. Topics
Deploying Machine Learning Algorithms
Sam PutnamQuality and Testing of Artificial Intelligence Algorithms
Best Practices
Activity - Kaggle
Best Practices
Questions & Terminology
Packages Exist
5/18/2017
4. Topics
Algorithms in the Media
Sam PutnamQuality and Testing of Artificial Intelligence Algorithms
Deploying Machine Learning Algorithms
Activity - Combating Bias In Your Business’ Algorithms
Success Stories
Challenges/Pushback
AI-First
5/3/2017
5. Topics
Enterprise Risk Mitigation Framework
Sam PutnamQuality and Testing of Artificial Intelligence Algorithms
Evaluating Vendors
Activity - Workshop Close
Public and Private Data Sources
Your Ecosystem
Artificial Intelligence Today
5/3/2017
6. Part 1 of 4
Machine Learning Algorithms in Production
Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Machine Learning Algorithms in Production
5/3/2017
7. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Machine Learning Algorithms in Production
5/3/2017
http://benanne.github.io/2014/08/05/spotify-cnns.html
8. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Machine Learning Algorithms in Production
5/3/2017
9. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Machine Learning Algorithms in Production
Activity - Name, Short
Professional Bio, Interest in
this Workshop
5/3/2017
10. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Machine Learning Algorithms in Production
5/3/2017http://www.r2d3.us/visual-intro-to-machine-learning-part-1/
11. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Machine Learning Algorithms in Production
5/3/2017
https://www.youtube.com/watch?v=JHQ0Qv0l54U
12. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Machine Learning Algorithms in Production
5/3/2017
https://www.youtube.com/watch?v=6YJRujHRbb8
13. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Machine Learning Algorithms in Production
5/3/2017
http://deeplearning.lipingyang.org/2016/11/16/how-neural-networks-recognize-a-dog-in-a-photo/
14. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Machine Learning Algorithms in Production
5/3/2017
https://backchannel.com/inside-facebooks-ai-machine-7a869b922ea7
15. Part 2 of 4
Deploying Machine Learning Algorithms
Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Deploying Machine Learning Algorithms
5/3/2017
16. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Deploying Machine Learning Algorithms
5/3/2017
http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf
17. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Deploying Machine Learning Algorithms
5/3/2017http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf
18. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Deploying Machine Learning Algorithms
5/3/2017
http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf
19. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Deploying Machine Learning Algorithms
5/3/2017
http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf
20. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Deploying Machine Learning Algorithms
5/3/2017
http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf
21. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Deploying Machine Learning Algorithms
Activity
Self-paced
1) Run Code
https://www.kaggle.com/sharmasanthosh/exploratory-
study-on-ml-algorithms
2) Collaborate with Neighbor on Questions
or
3) Ask Me
5/3/2017
22. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Deploying Machine Learning Algorithms
5/3/2017
http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf
23. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Deploying Machine Learning Algorithms
5/3/2017
http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf
24. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Deploying Machine Learning Algorithms
5/3/2017http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf
25. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Deploying Machine Learning Algorithms
5/3/2017
http://p.migdal.pl/2017/04/30/teaching-deep-learning.html
26. Part 3 of 4
Algorithms in the Media
Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Algorithms in the Media
5/3/2017
27. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Algorithms in the Media
5/3/2017
https://www.dailydot.com/debug/google-voice-recognition-gender-bias/
28. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Algorithms in the Media
5/3/2017
http://www.businessinsider.com/predictive-policing-discriminatory-police-crime-2016-10
29. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Algorithms in the Media
5/3/2017
http://www.independent.co.uk/life-style/gadgets-and-tech/news/googles-algorithm-shows-prestigious-job-ads-to-men-but-not-to-
women-10372166.html
30. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Algorithms in the Media
5/3/2017
http://dilbert.com/strip/2013-02-02
31. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Algorithms in the Media
Activity
1) What part of your business could be
affected by algorithms?
2) How could these algorithms be biased?
3) How could you mitigate this?
5/3/2017
32. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Algorithms in the Media
5/3/2017
http://www.economist.com/news/business/21720675-firm-using-algorithm-designed-cern-laboratory-how-germanys-otto-uses
33. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Algorithms in the Media
5/3/2017http://www.newyorker.com/magazine/2017/04/03/ai-versus-md
34. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Algorithms in the Media
5/3/2017
https://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html?_r=0
35. Part 4 of 4
Enterprise Risk Mitigation Framework
Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Enterprise Risk Mitigation Framework
5/3/2017
36. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Enterprise Risk Mitigation Framework
5/3/2017
https://blog.ycombinator.com/how-to-know-when-products-actually-use-ai/
can’t find original source. know it? email me - sam@EDeepLearning.com - I’ll add it
37. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Enterprise Risk Mitigation Framework
5/3/2017
https://blog.ycombinator.com/how-to-know-when-products-actually-use-ai/https://xkcd.com/1425/
38. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Enterprise Risk Mitigation Framework
5/3/2017
https://blog.ycombinator.com/how-to-know-when-products-actually-use-ai/
https://play.google.com/store/apps/details?id=com.google.android.googlequicksearchbox&hl=en
39. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Enterprise Risk Mitigation Framework
Activity
1) What did you learn?
2) What did you wish you could have learned?
3) What are you going to bring back to your
career?
5/3/2017
40. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Enterprise Risk Mitigation Framework
5/3/2017
https://blog.ycombinator.com/how-to-know-when-products-actually-use-ai/
https://twitter.com/fchollet/status/792960796133163008
41. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Enterprise Risk Mitigation Framework
5/3/2017https://blog.ycombinator.com/how-to-know-when-products-actually-use-ai/
https://medium.com/@ageitgey/machine-learning-is-fun-part-3-deep-learning-and-convolutional-neural-networks-f40359318721
42. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Enterprise Risk Mitigation Framework
5/3/2017
https://blog.ycombinator.com/how-to-know-when-products-actually-use-ai/
can’t find original source. know it? email me - sam@EDeepLearning.com - I’ll add it
43. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Enterprise Risk Mitigation Framework
1. Search
‘Deep Learning’
2. Listen 5/3/2017
44. Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Enterprise Risk Mitigation Framework
Artificial Intelligence
5/3/2017
https://blog.ycombinator.com/how-to-get-into-natural-language-processing/
45. Topics
Machine Learning Algorithms in Production
Deploying Machine Learning Algorithms
Algorithms in the Media
Enterprise Risk Mitigation Framework
Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
5/3/2017
46. Thank you
Always looking for new members & new locations in Cambridge, US or
NYC & new speakers to present on Deep Learning in Production topics
Thank you to the Machine Learning Society and Anna Royzman
Quality and Testing of Artificial Intelligence Algorithms Sam Putnam
Thank you to Google, Amazon, Facebook, YC, DARPA, Others who have
published diagrams and photos. Slides are for today only. 5/3/2017
https://www.slideshare.net/anirudhkoul/squeezing-deep-learning-into-mobile-phones/77