go

Recursos de programación de go
¿Y si lo escuchas mientras vas al trabajo o te pones en forma?: https://www.ivoox.com/46991733 ------------- El mundo del software ha sido largamente incomprendido y maltratado. Proyectos eternos, mal ejecutados, con resultados muy dispares y, demasiadas veces, con productos entregados de muy baja calidad. Lo importante era llegar en la fecha marcada por personas lejos de las trincheras. Indirecciones en las contrataciones, separación entre thinkers y doers, foco únicamente en “picar” y poco en revisar “cómo picamos”. Con este panorama, era prácticamente imposible pensar en una gran revolución digital. En 2001 aparece el Agile Manifesto, un documento que recoge el espíritu de nuevas prácticas de desarrollo de software muy exitosas que buscan ordenar lo que está desordenado. Entre ellas destacan Extreme Programming y Scrum. Año 2019, España. Los últimos 4 años han supuesto la explosión de Agile en el sector tecnológico español. Las empresas se han dado cuenta que necesitan introducir cambios profundos en la manera en que funcionan. Las empresas ya no son bancos, escuelas o retailers, sino empresas tecnológicas que operan en diferentes mercados. Para ser competitivas han buscado nuevos modelos organizacionales (equipos multidisciplinares, descentralización de la toma de decisiones, conexión continua con los clientes…), pero parece que aún no han comprendido que son EMPRESAS TECNOLÓGICAS. Esto se refleja en un exceso de atención al uso de Scrum y marcos de escalado y una escasa atención a la excelencia técnica y prácticas de desarrollo ágil de software, como XP o DevOps. Incluso en las principales citas entre profesionales del mundo Agile en España se presta una atención apenas residual al desarrollo de productos tecnológicos. ¿Qué nos está pasando? ¿Qué huecos estamos dejando sin cubrir? ¿Por qué? ¿Qué podemos hacer cada uno de nosotros para revertir esta situación? Hay una buena noticia: no estamos más que empezando. Estamos a tiempo de entender el poder que todos y cada uno de nosotros ostentamos para diseñar un futuro mejor, más ilusionante, en el que la tecnología bien hecha sea la protagonista. Un futuro en el que nuestras vidas tengan mucha más calidad gracias a la tecnología. Con esta charla queremos compartir nuestra visión desde los ámbitos de la consultoría y el desarrollo de productos software, dibujar un futuro ilusionante y empoderar a todos para que pasemos de ser espectadores a actores claves en el futuro del desarrollo de software en nuestro país. ------------- Todos los vídeos de la Cas 2019 en: https://lk.autentia.com/CAS-YouTube ¡Conoce Autentia! Twitter: https://goo.gl/MU5pUQ Instagram: https://lk.autentia.com/instagram LinkedIn: https://goo.gl/2On7Fj/ Facebook: https://goo.gl/o8HrWX
The coming decade promises to be extremely exciting for astronomers and data/computer scientists alike with the coming of Large Synoptic Survey Telescope (LSST), James Webb Space Telescope, and others. These projects will produce a huge amounts of data that need to be searched, corellated, analyzed and learned from in order to find answers to the questions, such as “What are Dark Energy and Dark Matter?”, “How did our Universe form?”, “How many Earth-threatening asteroids are out there?” LSST with its unique architecture will go both “wide” and “deep”, meaning that it will acquire images of large parts of the sky capturing the most distant galaxies. It will continually scan the visible sky during the period of 10 years and will produce the first video of the Universe in history. These new and exciting times require new tools that will help astronomers perform these analytical tasks more efficiently. In collaboration with astronomers from the University of Washington I built AXS, Astronomy Extensions for Spark, a tool based on Apache Spark, designed for fast cross-matching of astronomical catalogs and easy astronomical data processing. In this talk I will go through details of AXS’ architecture and explain why it is so fast. #BIGTH19 #Analytics #MachineLearning #Spark Session presented at Big Things Conference 2019 by Petar Zečević, CTO at SV Group. 20th November 2019 Kinépolis, Madrid Do you want to know more? https://www.bigthingsconference.com/
Whether you’re coming from the Android world or not, you’ve probably heard about Kotlin (the programming language) and its asynchronous programming concept called Coroutines. It’s a neat concept that helps you create execution blocks similar to light-weight threads, while at the same time allowing you to write your asynchronous code in a synchronous fashion. On the other hand, many of us got really (really) used to Reactive Extensions in many languages, and we prefer to go down this road. With ReactiveX, you can chain your asynchronous blocks in future-like structures, and easily control threading around them. Well, you know how it usually goes - you read about something (aha! what is this coroutines thing)… maybe you see a couple of talks on the topic, maybe you get interested. After you try it out and decide to use it in a real project, you start typing your code… and boom! Your program crashes. You then go to StackOverflow to check for answers to your problem, and surprise: you’re not handling errors properly. You copy-paste the solution without any edits or tests and you’re ready for release. Hopefully this is not you. You want to check everything before using a new language or library, you want to fully understand the consequences of switching over to a different solution from the one you currently have. There are some quirks in every approach, sure, but do you know all of the corner cases? That’s why we need to have this talk. Let’s go together through the most interesting examples of how we can get (and handle) errors with ReactiveX and Coroutines. ------------- Todos los vídeos de DevFest 2019 en :https://lk.autentia.com/DevFest-YT ¡Conoce Autentia! Twitter: https://goo.gl/MU5pUQ Instagram: https://lk.autentia.com/instagram LinkedIn: https://goo.gl/2On7Fj/ Facebook: https://goo.gl/o8HrWX
¿Y si lo escuchas mientras vas al trabajo o te pones en forma?: https://www.ivoox.com/46849161 ------------- Hablamos mucho de los modelos de cambio, de cómo transformar, de los propósitos evolutivos, de los objetivos y resultados clave que nos harán notar cómo estamos en ese proceso de cambio... pero no se habla mucho del "descoloque" previo, de eso que nos hace cambiar, y de cómo muchas veces, casi sin darnos cuenta, las organizaciones (y sí, también las personas) saltamos rápidamente a la acción y a la solución deseada... limitada por la situación o el contexto que precisamente hace que queramos cambiar. ------------- Todos los vídeos de la Cas 2019 en: https://lk.autentia.com/CAS-YouTube ¡Conoce Autentia! Twitter: https://goo.gl/MU5pUQ Instagram: https://lk.autentia.com/instagram LinkedIn: https://goo.gl/2On7Fj/ Facebook: https://goo.gl/o8HrWX
In this talk, Theofilos Kakantousis present TFX on Hopsworks, a fully open-source platform for running TFX pipelines on any cloud or on-premise. Hopsworks is a project-based multi-tenant platform for both data parallel programming and horizontally scalable machine learning pipelines. Hopsworks supports Apache Flink as a runner for Beam jobs and TFX pipelines are supported through Airflow support in Hopsworks. We will demonstrate how to build a ML pipeline with TFX, Beam’s Python API and the Flink Runner by using Jupyter notebooks, explain how security is transparently enabled with short-lived TLS certificates, and go through all the pipeline steps, from Data Validation, to Transformation, Model training with TensorFlow, Model Analysis, Model Serving and Monitoring with Kubernetes. #BIGTH19 #BigData #DeepLearning Session presented at Big Things Conference 2019 by Theofilos Kakantousis, Data Engineer & COO at Logical Clocks. 21st November 2019 Kinépolis, Madrid Do you want to know more? https://www.bigthingsconference.com/
¿Y si lo escuchas mientras vas al trabajo o te pones en forma?: https://www.ivoox.com/45640211 ------------- It's 2019. Teams are independent and we don't have a monolith anymore. We were told that with microservices we could keep our core functionality working while less important parts of the system are slow or even down. The problem is: designing distributed systems is not an easy task. The network is unreliable, services fail and there are lots of moving parts. At FREE NOW, being able to resist partial failure is an essential requirement. We need to ensure that our customers have a smooth user experience, getting a taxi home or running into the airport, even when things go wrong in our system. FREE NOW's platform depends on ~250 services that might fail at any time. This talk is focused on how we achieve fault-tolerance and what we learned during this journey. I will discuss resilience techniques that we use and how they can be useful to your business as well. Idempotence, retries, health checks, rate limiting, bulkhead and circuit breaking concepts, together with some real-world examples are on the agenda. ------------- Todos los vídeos de Commitconf 2019 en: https://lk.autentia.com/Commit19-YouTube ¡Conoce Autentia! Twitter: https://goo.gl/MU5pUQ Instagram: https://lk.autentia.com/instagram LinkedIn: https://goo.gl/2On7Fj/ Facebook: https://goo.gl/o8HrWX
The Artificial Vision area seeks to introduce this technology to everyone involved in the technological field. In particular, the stages that a company’s process had to go through are described until it reaches the optimum point for the transition to an AI. At this point, a parallel approach is made to explain how a data scientist can perform a feature engineering task but this time it is applied to the world of imaging. After covering these initial points, a deeper focus will be exposed in a case of use of detection and classification of defects applied in several industries (energy, industry 4.0, insurance). #BIGTH19 #AI #MachineLearning Session presented at Big Things Conference 2019 by David López Recio, AI Project Manager at Minsait. 20th November 2019 Kinépolis, Madrid Do you want to know more? https://www.bigthingsconference.com/
How does the visual representation of the world is structured by the brain? How could it be useful to react adaptively to new situations and scenarios? What if an autonomous system could learn that behavior? Recent Computer Vision and Deep Learning techniques enable the possibility to solve complex visual problems. One desirable property for most applications is the dynamic adaptation ability of the system to unknown contexts. This ability could be useful in a software production environment, where the data dynamics are business and human behavior dependent, providing flexibility while keeping robustness. This concept upgrades a trainable solution to a self-adaptive solution that we will go through during this talk. #BIGTH19 #AI #ComputerVision #DeepLearning Session presented at Big Things Conference 2019 by Javier Martínez Cebrián, Deep Learning & AI Specialist at BBVA Next Technologies, and Miguel Ángel Fernández, Assistant Professor and Researcher at Carlos III University. 20th November 2019 Kinépolis, Madrid Do you want to know more? https://www.bigthingsconference.com/
In this talk, Carlos Herrera will start describing the phases of a Data & Research project within Cabify, and how the different roles play together across each of them. First we will see Problem Dimensioning, which starts with more or less anecdotal evidence and finishes when we have rigorously estimated the size of the problem or opportunity. If the dimensioning points to a high impact possible solution, we go to Model Prototyping, where we aim to find the simplest possible model that solves the problem to the extent we are aiming for. This phase typically includes some testing, either against cold data from the archive or real time listening to the marketplace but avoiding to affect a user, so we can take bigger risks. If a viable model is found, next phase is Industrialisation when go full engineering mode to make sure we build a fully monitored, cost efficient, highly scalable, highly reliable solution able to cope with our always growing volumes. At last we have the Inference phase, where we aim to establish a causal relationship between the improvement we are deploying and some measurable experience of our drivers, riders and companies. #BIGTH19 #BigData #Cloud #MachineLearning Session presented at Big Things Conference 2019 by Carlos Herrera, VP of Data & Research at Cabify. 20th November 2019 Kinépolis, Madrid Do you want to know more? https://www.bigthingsconference.com/
Su charla completa sobre este tema: https://youtu.be/H37LuAeBGiA ------------- 1. 15 minutos, un microservicio, !Qué fácil parece! ¿Cuáles crees que deberían ser los siguientes pasos que tiene que dar una persona que quiere saber más del tema de los microservicios? 2. ¿Qué crees que es importante y no te ha dado tiempo a contar? ------------- Todos los vídeos de WTMZ 2019 en: https://lk.autentia.com/WTMZ-YouTube ¡Conoce Autentia! Twitter: https://goo.gl/MU5pUQ Instagram: https://lk.autentia.com/instagram LinkedIn: https://goo.gl/2On7Fj/ Facebook: https://goo.gl/o8HrWX