Experimentación ágil de machine learning con DVC
•
1 like•196 views
Conforme aumenta el uso de modelos de machine learning en las empresas, y se requiere continuamente estarlos enriqueciendo y generando experimentos para estimar el impacto de los cambios, requerimos de herramientas que nos apoyen para facilitar, automatizar y gestionar estas tareas. Presentado por: Ramón Valles
Report
Share
Report
Share
Recommended
Software Prototyping
The document discusses software prototyping. It defines prototyping as building initial versions of a software application that demonstrate functionality but may not contain the full logic of the final product. This allows getting early feedback from customers to better understand requirements. Different types of prototyping are covered, including throwaway, evolutionary, incremental, and extreme prototyping. The document also reviews best practices like reviewing prototypes with stakeholders and revising based on feedback. Potential applications and pros and cons of prototyping are presented.
Odinstar 2017 - Real World Automating to Support Testing
This document discusses strategies for automating testing tasks. It explores the difference between automating tactically and strategically. Tactical automation focuses on short-term goals like getting work done quickly, while strategic automation has agreed upon long-term goals. The document recommends automating flows through the system, abstracting the execution, and using multiple layers of abstraction. This helps create automation that is robust, flexible to change, and easy to maintain over time.
Test automation: Are Enterprises ready to bite the bullet?
This whitepaper talks about the actual challenges in implementing a successful Test Automation process. It give a glimpse of the 3Ws and 1H(Why, When, What & How) of automation and explains how the cost factor is just a myth. Eventually it talks about how Continuous Innovation with opensource tools together with a robust framework and business focused testing approach can lead to a successful test automation implementation.
Automating Pragmatically - Testival 20190604
# Automating Pragmatically
Testival Meetup 20190604
## Alan Richardson
- EvilTester.com
- @EvilTester
- compendiumdev.co.uk
- digitalonlinetactics.com
---
~~~~~~~~
Title: Automating Pragmatically
The online discussions of automating can leave me confused.
- Should you automate through the GUI?
- Should GUI automating be banned?
- Do all testers need to code? Is automating part of testing
or not?
- Do we need to automate to get a job?
In this short session Alan will discuss automating
from a pragmatic and contextual position and
share how he thinks about automating.
~~~~~~~~
A Software Problem (and a maybe-solution)
The document discusses problems in the software engineering field and proposes solutions. It identifies 4 main problems: 1) unsophisticated users require requirements analysts to create specifications, 2) non-programmers require programmers to develop minimally viable programs from specifications, 3) non-systems engineers require engineers to modify programs for scalability, and 4) a lack of standards leads to inefficient development. The document proposes addressing these by developing: A) a shared data structure, B) a user interface, C) a platform for minimal programs, D) software to generate standards-compliant applications, and E) framework extensions to guide further development. Ultimately, the document argues that vertically integrating software development from startups to enterprises could help solve large
How machine learning will affect software development
Machine learning will significantly impact software development in the following ways:
1) ML can analyze large amounts of machine data from software logs and metrics to improve security, performance, and reliability in an automated way that exceeds human capabilities.
2) ML techniques can be applied to code itself to automatically detect risky code, localize bugs, and provide intelligent IDE assistance across the entire development lifecycle.
3) ML has tremendous potential to continuously automate tasks like bug fixing, testing, deployment, and code optimization to deliver more and higher quality software faster with less human involvement.
Adrian Colyer - Keynote: NoSQL matters - NoSQL matters Dublin 2015
NoSQL matters, on that much I'm sure we can all agree. But if we take a closer look, what really matters when it comes to choosing a data store and/or a data processing platform? What really matters when it comes to getting the most out of that platform? And what is really going to matter as we take things to the next level?
Your data is in Prometheus, now what? (CurrencyFair Engineering Meetup, 2016)
Prometheus is a next-generation monitoring system with a time series database at it's core. Once you have a time series database, what do you do with it though? This talk will look at getting data in, and more importantly how to use the data you collect productively.
Contact us at prometheus@robustperception.io
Recommended
Software Prototyping
The document discusses software prototyping. It defines prototyping as building initial versions of a software application that demonstrate functionality but may not contain the full logic of the final product. This allows getting early feedback from customers to better understand requirements. Different types of prototyping are covered, including throwaway, evolutionary, incremental, and extreme prototyping. The document also reviews best practices like reviewing prototypes with stakeholders and revising based on feedback. Potential applications and pros and cons of prototyping are presented.
Odinstar 2017 - Real World Automating to Support Testing
This document discusses strategies for automating testing tasks. It explores the difference between automating tactically and strategically. Tactical automation focuses on short-term goals like getting work done quickly, while strategic automation has agreed upon long-term goals. The document recommends automating flows through the system, abstracting the execution, and using multiple layers of abstraction. This helps create automation that is robust, flexible to change, and easy to maintain over time.
Test automation: Are Enterprises ready to bite the bullet?
This whitepaper talks about the actual challenges in implementing a successful Test Automation process. It give a glimpse of the 3Ws and 1H(Why, When, What & How) of automation and explains how the cost factor is just a myth. Eventually it talks about how Continuous Innovation with opensource tools together with a robust framework and business focused testing approach can lead to a successful test automation implementation.
Automating Pragmatically - Testival 20190604
# Automating Pragmatically
Testival Meetup 20190604
## Alan Richardson
- EvilTester.com
- @EvilTester
- compendiumdev.co.uk
- digitalonlinetactics.com
---
~~~~~~~~
Title: Automating Pragmatically
The online discussions of automating can leave me confused.
- Should you automate through the GUI?
- Should GUI automating be banned?
- Do all testers need to code? Is automating part of testing
or not?
- Do we need to automate to get a job?
In this short session Alan will discuss automating
from a pragmatic and contextual position and
share how he thinks about automating.
~~~~~~~~
A Software Problem (and a maybe-solution)
The document discusses problems in the software engineering field and proposes solutions. It identifies 4 main problems: 1) unsophisticated users require requirements analysts to create specifications, 2) non-programmers require programmers to develop minimally viable programs from specifications, 3) non-systems engineers require engineers to modify programs for scalability, and 4) a lack of standards leads to inefficient development. The document proposes addressing these by developing: A) a shared data structure, B) a user interface, C) a platform for minimal programs, D) software to generate standards-compliant applications, and E) framework extensions to guide further development. Ultimately, the document argues that vertically integrating software development from startups to enterprises could help solve large
How machine learning will affect software development
Machine learning will significantly impact software development in the following ways:
1) ML can analyze large amounts of machine data from software logs and metrics to improve security, performance, and reliability in an automated way that exceeds human capabilities.
2) ML techniques can be applied to code itself to automatically detect risky code, localize bugs, and provide intelligent IDE assistance across the entire development lifecycle.
3) ML has tremendous potential to continuously automate tasks like bug fixing, testing, deployment, and code optimization to deliver more and higher quality software faster with less human involvement.
Adrian Colyer - Keynote: NoSQL matters - NoSQL matters Dublin 2015
NoSQL matters, on that much I'm sure we can all agree. But if we take a closer look, what really matters when it comes to choosing a data store and/or a data processing platform? What really matters when it comes to getting the most out of that platform? And what is really going to matter as we take things to the next level?
Your data is in Prometheus, now what? (CurrencyFair Engineering Meetup, 2016)
Prometheus is a next-generation monitoring system with a time series database at it's core. Once you have a time series database, what do you do with it though? This talk will look at getting data in, and more importantly how to use the data you collect productively.
Contact us at prometheus@robustperception.io
Humane assessment on cards
This set of cards provides a visual tour of the humane assessment method for making software engineering decisions.
TechEvent 2019: Artificial Intelligence in Dev & Ops; Martin Luckow - Trivadis
This document provides an overview of artificial intelligence trends and applications in development and operations. It discusses how AI is being used for rapid prototyping, intelligent programming assistants, automatic error handling and code refactoring, and strategic decision making. Examples are given of AI tools from Microsoft, Facebook, and Codota. The document also discusses challenges like interpretability of neural networks and outlines a vision of "Software 2.0" where programs are generated automatically to satisfy goals. It emphasizes that AI will transform software development over the next 10 years.
Bots for Crowds
Bots are able to perform repetitive actions, mimic human interaction and understand the world through sensors. Most of the existing bots are designed to serve individual users rather than integrating them as part of a group and attend different petitions by understanding the context and keeping track of the group task flow. The motivation is to understand which drivers are important to guarantee effective crowd interaction with bots and provide guidelines to platform designers. I have studied how bots can be useful in human environments such as education, social good, workplaces, and crowd marketplaces.
Over-Engineering: Causes, Symptoms, and Treatment
If your are using Cloud Foundry, you are most obviously into the microservices architecture and cloud-native app development approach. These are definitely best practices in modern application development, but too much of a good thing is good for nothing. Overuse of these principles may lead to over-engineering, when an application is split into too much microservices and, as such, gets hard to maintain and support. This presentation highlights how far overuse of the microservices concept can go, what issues exist, and how these issues can be avoided.
Software Quality and DevOps - Friends or Foes? @ Instituto Politécnico de Leiria
When we discuss DevOps from a software delivery perspective, all that we hear about is the need for speed: faster tests, more frequent deployments, cloud auto-scaling, and so on.
Does this mean we are going to break things more often as well? Maybe. But not necessarily. To go faster efficiently, we need to frequently deliver smaller changes with low risk. High performing organizations achieve this flow by applying a set of principles and practices that we will cover in this talk.
And, of course, they measure themselves!
Practical Test Automation Deep Dive
In this talk I'm going to focus on the technical aspects of 'test automation', using examples of approaches from a variety of Agile projects where we automated APIs, and GUIs. You'll learn about the use of abstractions and how to think about modeling the system in code to support automating it. Also how to use these abstractions to support stress testing, exploratory testing, ongoing CI assertions and the testing process in general. I'll also discuss the different styles of coding used to support automating tactically vs automating strategically.
Red lambda FAQ's
RedLambda (USA)
Red Lambda is an innovation company from Florida with 8 awarded patents and 8 others pending final award; focused on Cloud Security and Big Data Analytics technologies.
Red Lambda offers one unified, seamlessly integrated platform and a suite of bold solutions unlike anything in the industry today.
20+ top free tools essential for every software tester
This document provides a summary of 21 free and popular tools that are essential for testers. It begins by introducing the author and their consulting company. The document then lists and describes popular automation tools like Selenium, Appium, JUnit, and Jenkins. It also covers other useful tools for tasks like communication, documentation, API testing, load testing, and outsourcing small projects. The author emphasizes that the tools listed are recommendations based on their experience but that other favorites may exist.
Synergy of Human and Artificial Intelligence in Software Engineering
Keynote Talk by Tao Xie at International NSF sponsored Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE 2013) http://promisedata.org/raise/2013/
Blue Prism_White Paper_ Technical Kickstarter
This document provides an overview of common questions customers have when beginning an RPA deployment. It discusses considerations around choosing an RPA technology, including the importance of designing automations for longevity, reusability, and resilience. The document cautions against desktop recording approaches, noting they result in inflexible scripts that are difficult to maintain. It emphasizes the need for a centralized, model-based approach to building and running automations at scale across an enterprise. Security, control, and workflow are highlighted as important factors for ensuring governance and handling exceptions.
Why do most machine learning projects never make it to production
Cameron Vetter discusses common mistakes made in machine learning projects that prevent them from making it into production. Some key issues include a lack of leadership support and poorly defined goals, data science teams focusing only on model creation without ensuring it is production-ready, choosing overly complex projects instead of starting simple, having the wrong team composition without the needed roles, and not establishing proper processes around software development lifecycles, testing, and monitoring of models once in production. The presentation provides advice on how to address these problems such as gaining business buy-in, taking an iterative approach, evaluating existing solutions, and having the right team and processes in place.
Technovision
The document describes a Driverless ML API that was created to automate machine learning workflows including feature engineering, model validation, tuning, selection, and deployment. The API uses machine learning interpretability techniques to provide visualizations and explanations of models. It aims to help scale data science efforts and enable both expert and junior data scientists to more quickly develop accurate, production-ready models. Key capabilities of the API include automated exploratory data analysis, feature selection and engineering, model selection and hyperparameter tuning using GPUs for faster training, and model interpretability visualizations.
SW Engineering Management
- Software engineering is extremely complex and expensive work, with large software systems costing more than buildings and often having high failure rates.
- The two main factors that cause "runaway" software projects that exceed budgets and schedules are poor estimation done too early and unstable requirements that change frequently.
- Programmers are often given impossible tasks with too much work and not enough time, leading them to produce workarounds and quick fixes rather than well-designed solutions.
Digital to Physical: The Experiment Economy
Digital to Physical: The Experiment Economy
Read more at: https://www.meetup.com/producttanknyc/events/251428273/
When you wish to learn about a business or product idea, the last thing you want is to rely fully on your imagination. You want to get as close as possible to a real world interaction with the product or service you wish to provide. Even better - you want to see how real customers actually use it. While seeing the product on a computer screen is awesome, if it doesn’t look real and customers can't really interact with it - the feedback won’t be real. This is why we run experiments.
But why is it that "experimentation" is now considered a viable service offering for many companies today? We believe that the answers are in what we at ProductTank call the "Experiment Economy".
Over the last several years, we’ve seen the rise of a segment of the post-industrial economy called the "software-based economy" as companies like InVision, Pivotal and Alpha demonstrate levels of innovation driven by the need to run experiments before customers spend unnecessary amounts of money on the wrong ideas. We also see the rise of access to digital and physical products like MakerBot 3D Printers that give creators the ability to test and launch physical products faster.
Let's come together to discuss how this experiment economy has done wonders for product designers and how we can continue to benefit from the ramifications and create more opportunities for innovation. It stands to reason that as this experiment economy matures, product people will continue to evolve in their roles. We believe it is safe to assume that we’re in the midst of an experiment "gold rush" as we continue to discover how we can make digital and physical products better.
Our guest panelists:
Michelle M. Chu, Senior Product Manager / Head of Design at Alpha
https://www.linkedin.com/in/michellechu/
Shanfan Huang, Product Designer at Pivotal
https://www.linkedin.com/in/shanfan-huang-3930616b/
Jonathan Schwartz, Co-Founder & CPO at Voodoo Manufacturing
https://www.linkedin.com/in/jmschwartz11/
John Marcantonio, VP of Product at MakerBot
https://www.linkedin.com/in/johnlmarcantonio/
The Machine Learning Audit. MIS ITAC 2017 Keynote
As it gains wider adoption, what does machine learning mean for internal auditors and their organizations? With the proliferation of buzzwords and the black box nature of machine learning, Mr. Clark will help you cut through the noise and understand what fundamental changes are occurring and what is still more hype than reality. The session will include an overview of what machine learning is, examine its current and potential impact on industries and organizations, and explain the need for an objective audit. The presentation will conclude with an example of what a machine learning audit would consist of, and what steps would be required to perform one.
Jagrat_Mankad
Jagrat Mankad has over 15 years of experience as a software developer and principal. He has expertise in C#, C/C++, Java, Python and SQL programming languages. Some of the applications he has worked on include an idea tracking tool called IdeaWorks, a test automation framework in Python, and several tools to aid in testing central systems. He is skilled in all phases of the software development life cycle from requirements gathering to delivery. He has a bachelor's degree in computer engineering and holds a US patent.
Responsible Microservices
This document discusses the benefits of adopting a microservices architecture, including enabling independent life cycles, independent scalability, and failure isolation. It provides examples of how microservices allow developing and deploying parts of an application independently, scaling specific services rather than the entire monolith, and isolating failures to prevent bringing down the whole system. The document advocates for a responsible and data-driven approach to migrating from a monolith to microservices over time.
The future of (Windows) operations #WinOps #DevOps
DevOpsGuys co-founder Steve Thair talks about the impact DevOps automation and Cloud Technologies will have on IT operations, and how you can change your skills to remain relevant
Can Computers Design? Presented at interaction16, March 2, 2016, Helsinki by ...
The document discusses how computational methods and machine learning could potentially be used to automate aspects of interface design. It begins by providing background on how previous research has explored using optimization algorithms and predictive models from psychology to generate keyboard layouts and other interface designs. The document then discusses challenges, noting that interface design problems involve large search spaces and complex evaluation functions. It argues that a coordinated effort is needed to develop methods that can produce good outcomes while being compatible with design practice. Overall, the document explores the possibility of using computational approaches to automate parts of interface design, while acknowledging the difficulties in developing generally applicable methods.
DevOps Roadtrip Minneapolis
We’ve hit the road and rounded up local industry leaders Heather Mickman, Bridget Kromhout, Andy Domeier, and Ben Overmyer for this incredible half-day event. These speakers, from Target, Pivotal, Minneapolis Star Tribune, and SPS Commerce, shared real-life DevOps implementation stories and suggestions to help you on your DevOps journey.
Hola Mundo del Internet de las Cosas
El documento presenta información sobre diferentes componentes electrónicos como resistores, condensadores, diodos y potenciómetros. También describe circuitos integrados, Arduino, Raspberry Pi y cómo encender y apagar LEDs usando estos dispositivos de forma básica.
Estructuras de datos avanzadas: Casos de uso reales
La utilización de estructuras de datos adecuadas para cada problema hace que se simplifiquen en gran medida los tiempos de respuestas y la cantidad de cómputo realizada.
Por Nelson González
More Related Content
Similar to Experimentación ágil de machine learning con DVC
Humane assessment on cards
This set of cards provides a visual tour of the humane assessment method for making software engineering decisions.
TechEvent 2019: Artificial Intelligence in Dev & Ops; Martin Luckow - Trivadis
This document provides an overview of artificial intelligence trends and applications in development and operations. It discusses how AI is being used for rapid prototyping, intelligent programming assistants, automatic error handling and code refactoring, and strategic decision making. Examples are given of AI tools from Microsoft, Facebook, and Codota. The document also discusses challenges like interpretability of neural networks and outlines a vision of "Software 2.0" where programs are generated automatically to satisfy goals. It emphasizes that AI will transform software development over the next 10 years.
Bots for Crowds
Bots are able to perform repetitive actions, mimic human interaction and understand the world through sensors. Most of the existing bots are designed to serve individual users rather than integrating them as part of a group and attend different petitions by understanding the context and keeping track of the group task flow. The motivation is to understand which drivers are important to guarantee effective crowd interaction with bots and provide guidelines to platform designers. I have studied how bots can be useful in human environments such as education, social good, workplaces, and crowd marketplaces.
Over-Engineering: Causes, Symptoms, and Treatment
If your are using Cloud Foundry, you are most obviously into the microservices architecture and cloud-native app development approach. These are definitely best practices in modern application development, but too much of a good thing is good for nothing. Overuse of these principles may lead to over-engineering, when an application is split into too much microservices and, as such, gets hard to maintain and support. This presentation highlights how far overuse of the microservices concept can go, what issues exist, and how these issues can be avoided.
Software Quality and DevOps - Friends or Foes? @ Instituto Politécnico de Leiria
When we discuss DevOps from a software delivery perspective, all that we hear about is the need for speed: faster tests, more frequent deployments, cloud auto-scaling, and so on.
Does this mean we are going to break things more often as well? Maybe. But not necessarily. To go faster efficiently, we need to frequently deliver smaller changes with low risk. High performing organizations achieve this flow by applying a set of principles and practices that we will cover in this talk.
And, of course, they measure themselves!
Practical Test Automation Deep Dive
In this talk I'm going to focus on the technical aspects of 'test automation', using examples of approaches from a variety of Agile projects where we automated APIs, and GUIs. You'll learn about the use of abstractions and how to think about modeling the system in code to support automating it. Also how to use these abstractions to support stress testing, exploratory testing, ongoing CI assertions and the testing process in general. I'll also discuss the different styles of coding used to support automating tactically vs automating strategically.
Red lambda FAQ's
RedLambda (USA)
Red Lambda is an innovation company from Florida with 8 awarded patents and 8 others pending final award; focused on Cloud Security and Big Data Analytics technologies.
Red Lambda offers one unified, seamlessly integrated platform and a suite of bold solutions unlike anything in the industry today.
20+ top free tools essential for every software tester
This document provides a summary of 21 free and popular tools that are essential for testers. It begins by introducing the author and their consulting company. The document then lists and describes popular automation tools like Selenium, Appium, JUnit, and Jenkins. It also covers other useful tools for tasks like communication, documentation, API testing, load testing, and outsourcing small projects. The author emphasizes that the tools listed are recommendations based on their experience but that other favorites may exist.
Synergy of Human and Artificial Intelligence in Software Engineering
Keynote Talk by Tao Xie at International NSF sponsored Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE 2013) http://promisedata.org/raise/2013/
Blue Prism_White Paper_ Technical Kickstarter
This document provides an overview of common questions customers have when beginning an RPA deployment. It discusses considerations around choosing an RPA technology, including the importance of designing automations for longevity, reusability, and resilience. The document cautions against desktop recording approaches, noting they result in inflexible scripts that are difficult to maintain. It emphasizes the need for a centralized, model-based approach to building and running automations at scale across an enterprise. Security, control, and workflow are highlighted as important factors for ensuring governance and handling exceptions.
Why do most machine learning projects never make it to production
Cameron Vetter discusses common mistakes made in machine learning projects that prevent them from making it into production. Some key issues include a lack of leadership support and poorly defined goals, data science teams focusing only on model creation without ensuring it is production-ready, choosing overly complex projects instead of starting simple, having the wrong team composition without the needed roles, and not establishing proper processes around software development lifecycles, testing, and monitoring of models once in production. The presentation provides advice on how to address these problems such as gaining business buy-in, taking an iterative approach, evaluating existing solutions, and having the right team and processes in place.
Technovision
The document describes a Driverless ML API that was created to automate machine learning workflows including feature engineering, model validation, tuning, selection, and deployment. The API uses machine learning interpretability techniques to provide visualizations and explanations of models. It aims to help scale data science efforts and enable both expert and junior data scientists to more quickly develop accurate, production-ready models. Key capabilities of the API include automated exploratory data analysis, feature selection and engineering, model selection and hyperparameter tuning using GPUs for faster training, and model interpretability visualizations.
SW Engineering Management
- Software engineering is extremely complex and expensive work, with large software systems costing more than buildings and often having high failure rates.
- The two main factors that cause "runaway" software projects that exceed budgets and schedules are poor estimation done too early and unstable requirements that change frequently.
- Programmers are often given impossible tasks with too much work and not enough time, leading them to produce workarounds and quick fixes rather than well-designed solutions.
Digital to Physical: The Experiment Economy
Digital to Physical: The Experiment Economy
Read more at: https://www.meetup.com/producttanknyc/events/251428273/
When you wish to learn about a business or product idea, the last thing you want is to rely fully on your imagination. You want to get as close as possible to a real world interaction with the product or service you wish to provide. Even better - you want to see how real customers actually use it. While seeing the product on a computer screen is awesome, if it doesn’t look real and customers can't really interact with it - the feedback won’t be real. This is why we run experiments.
But why is it that "experimentation" is now considered a viable service offering for many companies today? We believe that the answers are in what we at ProductTank call the "Experiment Economy".
Over the last several years, we’ve seen the rise of a segment of the post-industrial economy called the "software-based economy" as companies like InVision, Pivotal and Alpha demonstrate levels of innovation driven by the need to run experiments before customers spend unnecessary amounts of money on the wrong ideas. We also see the rise of access to digital and physical products like MakerBot 3D Printers that give creators the ability to test and launch physical products faster.
Let's come together to discuss how this experiment economy has done wonders for product designers and how we can continue to benefit from the ramifications and create more opportunities for innovation. It stands to reason that as this experiment economy matures, product people will continue to evolve in their roles. We believe it is safe to assume that we’re in the midst of an experiment "gold rush" as we continue to discover how we can make digital and physical products better.
Our guest panelists:
Michelle M. Chu, Senior Product Manager / Head of Design at Alpha
https://www.linkedin.com/in/michellechu/
Shanfan Huang, Product Designer at Pivotal
https://www.linkedin.com/in/shanfan-huang-3930616b/
Jonathan Schwartz, Co-Founder & CPO at Voodoo Manufacturing
https://www.linkedin.com/in/jmschwartz11/
John Marcantonio, VP of Product at MakerBot
https://www.linkedin.com/in/johnlmarcantonio/
The Machine Learning Audit. MIS ITAC 2017 Keynote
As it gains wider adoption, what does machine learning mean for internal auditors and their organizations? With the proliferation of buzzwords and the black box nature of machine learning, Mr. Clark will help you cut through the noise and understand what fundamental changes are occurring and what is still more hype than reality. The session will include an overview of what machine learning is, examine its current and potential impact on industries and organizations, and explain the need for an objective audit. The presentation will conclude with an example of what a machine learning audit would consist of, and what steps would be required to perform one.
Jagrat_Mankad
Jagrat Mankad has over 15 years of experience as a software developer and principal. He has expertise in C#, C/C++, Java, Python and SQL programming languages. Some of the applications he has worked on include an idea tracking tool called IdeaWorks, a test automation framework in Python, and several tools to aid in testing central systems. He is skilled in all phases of the software development life cycle from requirements gathering to delivery. He has a bachelor's degree in computer engineering and holds a US patent.
Responsible Microservices
This document discusses the benefits of adopting a microservices architecture, including enabling independent life cycles, independent scalability, and failure isolation. It provides examples of how microservices allow developing and deploying parts of an application independently, scaling specific services rather than the entire monolith, and isolating failures to prevent bringing down the whole system. The document advocates for a responsible and data-driven approach to migrating from a monolith to microservices over time.
The future of (Windows) operations #WinOps #DevOps
DevOpsGuys co-founder Steve Thair talks about the impact DevOps automation and Cloud Technologies will have on IT operations, and how you can change your skills to remain relevant
Can Computers Design? Presented at interaction16, March 2, 2016, Helsinki by ...
The document discusses how computational methods and machine learning could potentially be used to automate aspects of interface design. It begins by providing background on how previous research has explored using optimization algorithms and predictive models from psychology to generate keyboard layouts and other interface designs. The document then discusses challenges, noting that interface design problems involve large search spaces and complex evaluation functions. It argues that a coordinated effort is needed to develop methods that can produce good outcomes while being compatible with design practice. Overall, the document explores the possibility of using computational approaches to automate parts of interface design, while acknowledging the difficulties in developing generally applicable methods.
DevOps Roadtrip Minneapolis
We’ve hit the road and rounded up local industry leaders Heather Mickman, Bridget Kromhout, Andy Domeier, and Ben Overmyer for this incredible half-day event. These speakers, from Target, Pivotal, Minneapolis Star Tribune, and SPS Commerce, shared real-life DevOps implementation stories and suggestions to help you on your DevOps journey.
Similar to Experimentación ágil de machine learning con DVC (20)
TechEvent 2019: Artificial Intelligence in Dev & Ops; Martin Luckow - Trivadis
TechEvent 2019: Artificial Intelligence in Dev & Ops; Martin Luckow - Trivadis
Software Quality and DevOps - Friends or Foes? @ Instituto Politécnico de Leiria
Software Quality and DevOps - Friends or Foes? @ Instituto Politécnico de Leiria
20+ top free tools essential for every software tester
20+ top free tools essential for every software tester
Synergy of Human and Artificial Intelligence in Software Engineering
Synergy of Human and Artificial Intelligence in Software Engineering
Why do most machine learning projects never make it to production
Why do most machine learning projects never make it to production
The future of (Windows) operations #WinOps #DevOps
The future of (Windows) operations #WinOps #DevOps
Can Computers Design? Presented at interaction16, March 2, 2016, Helsinki by ...
Can Computers Design? Presented at interaction16, March 2, 2016, Helsinki by ...
More from Software Guru
Hola Mundo del Internet de las Cosas
El documento presenta información sobre diferentes componentes electrónicos como resistores, condensadores, diodos y potenciómetros. También describe circuitos integrados, Arduino, Raspberry Pi y cómo encender y apagar LEDs usando estos dispositivos de forma básica.
Estructuras de datos avanzadas: Casos de uso reales
La utilización de estructuras de datos adecuadas para cada problema hace que se simplifiquen en gran medida los tiempos de respuestas y la cantidad de cómputo realizada.
Por Nelson González
Building bias-aware environments
Onboarding new members into an engineering team is not easy on anyone. In a short period of time, the new team member is required to be able to bring professional
Por Victoriya Kalmanovich
El secreto para ser un desarrollador Senior
En esta charla platicaremos sobre el “secreto” y el camino para llegar a ser un desarrollador Senior, experiencia, consejos y recomendaciones que en estos 8 años
Por René Sandoval
Cómo encontrar el trabajo remoto ideal
Te compartiré las herramientas que yo he usado para buscar, encontrar y disfrutar el trabajo remoto durante los últimos 10 años.
Por Oscar Swanros
Automatizando ideas con Apache Airflow
Apache Airflow es una plataforma en la que podemos crear flujos de datos de manera programática, planificarlos y monitorear de manera centralizada.
Por Yesi Díaz
How thick data can improve big data analysis for business:
Este documento discute cómo el "thick data" (datos densos) provenientes de la antropología y la semiótica pueden ayudar a mejorar los análisis de big data en el mundo de los negocios. Explica que el thick data proporciona contexto social y significado que es clave para la interpretación de resultados de big data. Presenta dos estudios de caso donde el thick data ayudó a Netflix y a un banco francés a mejorar sus estrategias. Concluye que el big data provee respuestas pero se necesitan enfoques cualitativos para identificar los
Introducción al machine learning
Se brindará una introducción a las técnicas más utilizadas así como a algunas aplicaciones.
Por José Octavio Gutiérrez
Democratizando el uso de CoDi
CoDi® es la nueva forma de realizar pagos digitales desarrollada por el Banco de México. Por medio de CoDi puedes realizar cobros y pagos desde tu celular, utilizando una cuenta bancaria o de alguna institución financiera, sin comisiones.
Por Cristian Jaramillo
Gestionando la felicidad de los equipos con Management 3.0
En las metodologías agiles hablamos de equipos colaborativos, autogestionados y felices. hablamos de lideres serviciales. El management 3.0 nos ayuda a cultivar el mindset correcto, aquel que servirá como el terreno fértil para que la agilidad florezca.
Por Andrea Vélez Cárdenas
Taller: Creación de Componentes Web re-usables con StencilJS
Hoy por hoy las experiences de usuario pueden ser enriquecidas mediante el uso de Web Components, que son un estándar de la W3C soportado por la mayoría de los navegadores web modernos.
Por Alex Arriaga
El camino del full stack developer (o como hacemos en SERTI para que no solo ...
El documento describe los pasos para convertirse en un desarrollador fullstack, incluyendo el aprendizaje de back end, front end, bases de datos, seguridad, configuración de la pila tecnológica, análisis y diseño de requisitos, y administración de sistemas. Ser fullstack es un camino continuo que requiere constante aprendizaje y actualización de habilidades.
¿Qué significa ser un programador en Bitso?
Ser un programador en Bitso significa dominar varios lenguajes de programación como Java, PHP, React y plataformas móviles como iOS y Android, así como herramientas de desarrollo como Jenkins, Docker y Kubernetes. Bitso está buscando programadores talentosos que deseen aplicar a posiciones abiertas y puedan enviar su currículum a jobs@bitso.com.
Colaboración efectiva entre desarrolladores del cliente y tu equipo.
Este documento presenta estrategias para mejorar la colaboración entre equipos de desarrollo de clientes y proveedores. Se discuten temas como definir requerimientos de manera clara y completa, priorizar tareas, coordinar el trabajo cuando un proyecto ya está en progreso, y comunicarse de forma efectiva a través de reuniones periódicas y herramientas como chat. El objetivo general es sobrevivir a los desafíos de la colaboración mediante la implementación de mejores prácticas.
Pruebas de integración con Docker en Azure DevOps
Este documento describe cómo implementar pruebas de integración con Docker en Azure DevOps. Explica los conceptos de pruebas de integración, Docker y Azure DevOps. Luego detalla los pasos para crear una imagen Docker con SQL Server, ejecutar un contenedor Docker para las pruebas y configurar un pipeline en Azure DevOps para compilar la imagen, ejecutar el contenedor y realizar las pruebas de integración.
Elixir + Elm: Usando lenguajes funcionales en servicios productivos
En mi equipo de trabajo, decidimos utilizar Elm y Elixir para desarrollar la nueva version de la plataforma.
Presentado por Anayeli Malvaez
Así publicamos las apps de Spotify sin stress
En Spotify tenemos 1600+ ingenieros, trabajando en 280+ squads. Aún a esta escala, hemos logrado adoptar prácticas que nos han permitido acelerar la forma en que desarrollamos nuestro producto. Presentado por Erick Camacho en SG Virtual Conference 2020
Achieving Your Goals: 5 Tips to successfully achieve your goals
he measure of the executive, Peter F. Drucker reminds us, is the ability to "get the right things done." This involves having clarity on what are the right things as well as avoiding what is unproductive. Intelligence, creativity, and knowledge may all be wasted if not put to work on the things that matter.
Presentado por Cristina Nistor en SG Virtual Conference 2020
Acciones de comunidades tech en tiempos del Covid19
Este documento describe las acciones tomadas por varias comunidades tecnológicas en México para ayudar durante la pandemia de COVID-19, incluyendo el COVID-19 Challenge, COVID3DMX, y el Observatorio de Datos COVID MX. El COVID-19 Challenge fue un concurso para desarrollar soluciones para prevenir y difundir información sobre el virus. COVID3DMX conecta las necesidades médicas con proveedores de equipo médico. Y el Observatorio de Datos COVID MX realiza un seguimiento semanal de las tendencias del virus en México
De lo operativo a lo estratégico: un modelo de management de diseño
La charla presenta un modelo claro, generado por la ponente, para atender los niveles desde lo operativo a lo estratégico.
Presentado por Gabriela Salinas en SG Virtual Conference
More from Software Guru (20)
Estructuras de datos avanzadas: Casos de uso reales
Estructuras de datos avanzadas: Casos de uso reales
How thick data can improve big data analysis for business:
How thick data can improve big data analysis for business:
Gestionando la felicidad de los equipos con Management 3.0
Gestionando la felicidad de los equipos con Management 3.0
Taller: Creación de Componentes Web re-usables con StencilJS
Taller: Creación de Componentes Web re-usables con StencilJS
El camino del full stack developer (o como hacemos en SERTI para que no solo ...
El camino del full stack developer (o como hacemos en SERTI para que no solo ...
Colaboración efectiva entre desarrolladores del cliente y tu equipo.
Colaboración efectiva entre desarrolladores del cliente y tu equipo.
Elixir + Elm: Usando lenguajes funcionales en servicios productivos
Elixir + Elm: Usando lenguajes funcionales en servicios productivos
Achieving Your Goals: 5 Tips to successfully achieve your goals
Achieving Your Goals: 5 Tips to successfully achieve your goals
Acciones de comunidades tech en tiempos del Covid19
Acciones de comunidades tech en tiempos del Covid19
De lo operativo a lo estratégico: un modelo de management de diseño
De lo operativo a lo estratégico: un modelo de management de diseño
Recently uploaded
UiPath Test Automation using UiPath Test Suite series, part 6
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Epistemic Interaction - tuning interfaces to provide information for AI support
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
20240607 QFM018 Elixir Reading List May 2024
Everything I found interesting about the Elixir programming ecosystem in May 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
How to Get CNIC Information System with Paksim Ga.pptx
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Microsoft - Power Platform_G.Aspiotis.pdf
Revolutionizing Application Development
with AI-powered low-code, presentation by George Aspiotis, Sr. Partner Development Manager, Microsoft
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
20240605 QFM017 Machine Intelligence Reading List May 2024
Everything I found interesting about machines behaving intelligently during May 2024
A tale of scale & speed: How the US Navy is enabling software delivery from l...
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
20240609 QFM020 Irresponsible AI Reading List May 2024
Everything I found interesting about the irresponsible use of machine intelligence in May 2024
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar
Full-RAG: A modern architecture for hyper-personalization
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Recently uploaded (20)
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Epistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI support
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
A tale of scale & speed: How the US Navy is enabling software delivery from l...
A tale of scale & speed: How the US Navy is enabling software delivery from l...
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
Experimentación ágil de machine learning con DVC
- 1. Version Control for Machine Learning Projects @mroutis
- 2. About me - Name: Ramón Valles - Handle: mroutis - Work: Software developer - Company: iterative.ai @mroutis
- 4. Why versioning is important? @mroutis
- 5. Datasets evolve over time @mroutis
- 7. “Yea, we have version control” @mroutis https://www.reddit.com/r/ProgrammerHumor/comments/63rcvc/yea_we_have_version_control/
- 8. How do we identify each version? @mroutis
- 10. Manual work is error prone. @mroutis
- 11. Is versioning data / models enough? @mroutis
- 13. Reproducibility Crisis “I was recently chatting to a friend whose startup’s machine learning models were so disorganized... training the same model get different results!” - Peter Warden (2018) https://petewarden.com/2018/03/19/the-machine-learning-reproducibility-crisis/ @mroutis
- 14. @mroutis
- 15. What have been done so far to address this? @mroutis
- 17. Manual work is error prone. @mroutis
- 19. - Chain processes together - Reproduce in the correct order - Make it easier to return to old work - The output of one stage is the input of the next on @mroutis Pipelines
- 20. How does DVC address this problems? @mroutis
- 21. @mroutis
- 24. @mroutis
- 28. Want to learn more? - Check out docs: https://dvc.org/doc - Chat with us: https://dvc.org/chat - Contribute on GitHub: https://github.com/iterative/dvc - Follow us on Twitter: @DVCorg @mroutis
- 29. Thanks for listening! @mroutis Thanks for Listening - Chris Thile
- 30. Thanks for the invitation!