The document summarizes key points from a conference on November 9-10, 2015 about Gradle builds, Android performance, healthy code bases, and trending Android topics. It discusses optimizing Gradle builds for speed, including configuration on demand, the Gradle daemon, and avoiding expensive operations. It also covers measuring build times for different project sizes and configurations. Additional sections provide information on creating custom Gradle plugins, using data binding in Android, and new tools like Jack, Kotlin, and Eddystone beacons.
Google Cloud Dataflow can be used to build TensorFlow pipelines. Dataflow allows training multiple TensorFlow models in parallel and writing results to Cloud Datastore. A sample pipeline shows generating training parameters, mapping over them to train models, and writing accuracy results to Cloud Storage. Dataflow provides autoscaling and machine types can be configured. The new DatastoreIO allows reading from and writing to Cloud Datastore from Dataflow pipelines using Protobuf and entity conversion helpers.
The document is a presentation about Google Compute Engine (GCE). It discusses cloud computing service levels including Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). GCE is described as an IaaS offering that provides virtual machines with flexible configurations and pricing based on minute usage. A demo is shown creating a VM and hosting a website using Apache. Another demo spins up a Hadoop cluster on GCE for distributed data processing.
GAE是Googler的御用開發工具,從支援Python語言到Java、Go、PHP,Google的服務舉凡Gmail, Drive等等都是開發在GAE上,讓我們探索GAE的演進史以及讓人愛不釋手的功能
iOS 8 is finally here while the new iPhone 6 and iPhone 6 plus will appear in a few days. New APIs appears on scene, as well as new challenges to support the new screen sizes. I’ve been playing with the final version and here you have my findings.
The document provides an overview of Google App Engine (GAE), including available services, common use cases, and best practices for developing applications on the platform. It discusses how GAE offers scalable hosting as a Platform as a Service (PaaS), with free quotas and no server management required. The document also outlines common strategies for structuring GAE applications, accessing data storage and APIs, and deploying code.
This document provides an overview of Google Cloud Platform services including Compute Engine, networking, load balancing, logging, and monitoring. It discusses setting up a Google Cloud Project, using the web console and command line interface, creating VM instances, managing disks and images, configuring networking and firewall rules, implementing load balancing with target pools and forwarding rules, and auto-scaling instances. The document concludes by proposing a hands-on exercise to build an auto-scaling architecture with an Apache service and load balancer and test it using ab.
Slides from the Grails Integration Strategies BOF at JavaOne 2009. You can see these in context in a video shot by Bryan Williams of the Chicago Groovy User Group - http://cgug.blip.tv
The Grails' Resource Plugin allows for modular development of static resources like CSS, JavaScript, and images. It provides a processing pipeline that optimizes resources by bundling, minifying, compressing, and caching them. Developers declare resource dependencies and the plugin automatically includes the required resources on pages. This improves performance by reducing page load time through optimizations like minification and compression of files.
This document discusses the possibilities of WebGL and how it can be used for 3D graphics rendering on the web. It explains that WebGL allows for GPU-accelerated rendering directly in the browser by using APIs to control graphics processing units. It provides examples of using WebGL to initialize a WebGL context, create and compile shaders, and render 3D graphics by passing vertex and color data to shaders. The document recommends learning resources and frameworks for WebGL and suggests areas where WebGL could be applied, such as games, data visualization, and user interfaces.
The new static resources framework provides declarative resource management and optimization in Grails applications. The resources plugin allows resources like CSS, JavaScript, and images to be declared and then processed and optimized at runtime. This includes bundling, minification, caching, and more. The plugin uses a mapping pipeline to modify resources according to configurable mappers before delivery. This provides a major improvement over prior approaches by automating resource handling and optimization.
The document outlines a 30-day Google Cloud program for university students to prepare them for cloud careers. It includes two tracks: Cloud Engineering and Data Science & Machine Learning. The Cloud Engineering track covers foundational infrastructure tasks like deploying and managing cloud environments and Kubernetes. It also covers networking and security. The Data Science track covers data, machine learning, and AI tasks to prepare students for roles in data and business. Completing the tracks earns students participation certificates, skill badges, and prizes like t-shirts and laptop bags. The document provides an agenda for an introductory session that orients students to Google Cloud and walks through several hands-on labs.
This document provides an overview of using JavaScript to enhance SharePoint experiences. It discusses why JavaScript is useful, best practices, and several JavaScript libraries that can be used with SharePoint including utility libraries, data access libraries, application frameworks, and UI libraries. It also demonstrates how to register JavaScript on all pages in Office 365 and provides examples of Angular, jQuery, DataJS, and SPServices.
Google Cloud Networking provides a global, flexible, and secure networking foundation for applications and data. Key elements include: - A global fiber network with over 100 points of presence and hundreds of thousands of miles of cable connecting Google's regions and zones. - The Andromeda network virtualization stack, which powers VPC networking and provides scalable isolation, high performance, and distributed firewall capabilities. - Global and regional load balancing options like HTTP(S) and TCP/UDP load balancing for optimizing application delivery worldwide. - Hybrid connectivity options like Cloud Interconnect, VPN, and Direct Peering to build hybrid cloud architectures connecting on-premises to Google Cloud.
Drools 7.0 provides improvements to the Drools, jBPM, OptaPlanner, and DashBuilder products. These include upgrades to the execution server UI, process runtime views, and usability features like Pattern Fly. The products are integrated under the new KIE framework and utilize technologies like GWT, Errai, and UberFire for their rich client capabilities. The rule engine has been enhanced with capabilities like reactive lists, nested reactive patterns, and optimizations for scalability.
The document outlines two training tracks for Google Cloud - Cloud Engineering and Data Science & Machine Learning. The Cloud Engineering track includes labs on creating and managing cloud resources, performing infrastructure tasks, setting up cloud environments, deploying to Kubernetes, and building secure networks. The Data Science track focuses on foundational data and ML tasks, insights from BigQuery, engineering data, integrating with ML APIs, and explainable AI models. Completing the labs in each track earns skill badges that demonstrate proficiency in Google Cloud.
This document summarizes Google Cloud Platform (GCP) learning resources. It provides an overview of GCP services like Compute Engine, App Engine, and Cloud Storage. It then lists various official training resources from Google including courses, exams, and documentation. Links are also provided to the GCP blog, GitHub, and other sources of information about GCP.
Speaker: Martin Gannholm - Lead Engineer, Google Google Cloud Platform provides everything you need to build, run, and scale social, mobile, and online applications. Already, tens of thousands of popular applications like Khan Academy, Angry Birds, SnapChat, and Pulse are benefiting from the power of running on top of Google infrastructure. Come join Google as we go deep on how to best leverage our technology with RightScale to build your next masterpiece.
À l'automne dernier, nous avons eu la chance de développer une nouvelle app pour un de nos clients en partant de zéro. L'objectif ? Créer une application minimale à mettre entre les mains de dizaines de beta testeurs, en 8 semaines et avec 2 développeurs. Partant d'une feuille blanche, nous avons pu mettre en œuvre les dernières avancées de la stack Android sans être contraints par l'existant. Développeurs débutants comme expérimentés, vous repartirez de ce talk avec nos apprentissages clés sur l'architecture ainsi que sur les bibliothèques et astuces pour faciliter la maintenance et la stabilité de l'application. En bonus, nous répondrons à la question : "Une app full-compose, est-ce que c'est cool ?"
1. The document discusses integrating Webpack into a Django project to bundle static files. 2. It provides an example Django application and shows how to set up basic Webpack configuration to bundle Vue.js and other static files. 3. Additional Webpack features like hot reloading and code splitting are demonstrated to improve the development and production workflows.
The document summarizes a meetup on data streaming and machine learning with Google Cloud Platform. The meetup consisted of two presentations: 1. The first presentation discussed using Apache Beam (Dataflow) on Google Cloud Platform to parallelize machine learning training for improved performance. It showed how Dataflow was used to reduce training time from 12 hours to under 30 minutes. 2. The second presentation demonstrated building a streaming pipeline for sentiment analysis on Twitter data using Dataflow. It covered streaming patterns, batch vs streaming processing, and a demo that ingested tweets from PubSub and analyzed them using Cloud NLP API and BigQuery.
The document summarizes a meetup on data streaming and machine learning with Google Cloud Platform. The meetup consisted of two presentations: 1. The first presentation discussed using Apache Beam and Google Cloud Dataflow to parallelize machine learning training for hyperparameter optimization. It showed how Dataflow reduced training time from 12 hours to under 30 minutes. 2. The second presentation demonstrated building a streaming Twitter sentiment analysis pipeline with Dataflow. It covered streaming patterns, batch vs streaming considerations, and a demo that ingested tweets from PubSub, analyzed sentiment with NLP, and loaded results to BigQuery.
A presentation about the build tool grunt js JavaScript for web applications and node.js environments to achieve continous integration. David Amend
This document discusses high performance web application lifecycles. It covers trends in continuous integration, automated web performance testing, and continuous monitoring in production. Metrics like page load time, resource timing, and third party content load time are discussed. The document also covers browser APIs like Navigation Timing and Performance Timeline that provide performance metrics, and how these can be used to analyze performance across builds and detect common problems. Limitations include lack of support in older browsers and inability to provide insight into JavaScript.
Slow builds have been plaguing Android development since the very beginning, especially for large multi-dex projects. As libraries tend to grow in size and the more libraries an application consumes it will slow down the build, especially when an application goes over the mutli-dex limit. Libraries aren't the only thing that can slow down the build, adding many Gradle plugins and repositories can increase the time it takes to configure the Gradle build. This talk will be centered around how I was able to decrease Yammer for Android's Gradle build times by optimizing our use of the Android Gradle plugin and the Gradle setup of our multi-project build and will give several tools and tips on how to help you profile and decrease your build times as well.
The document discusses adaptive images in responsive web design. It begins by explaining why the browser should be asked for information like screen resolution and bandwidth instead of doing speed tests. It then covers different techniques for adaptive images like using the browser width, screen resolution, bandwidth tests, feature testing vs browser sniffing, and CSS media queries. It also discusses workarounds like using the .htaccess file, <picture> element, and HiSRC plugin to serve responsive images. The document advocates for newer approaches that provide a simple user experience while allowing the browser and server to communicate information.
This document provides an overview of AngularJS. It begins with introductions and then outlines the agenda which includes bootstrapping, why AngularJS is useful, main features like templating and data binding, best practices, testing and tooling, SEO considerations, and whether it can be used for enterprise projects. It then demonstrates some AngularJS concepts like directives and templating. The document emphasizes AngularJS' reusability, testability, and production readiness while noting best practices are important for complex projects.
The document discusses optimization of the presentation tier of web applications. It notes that the presentation tier is often overlooked despite being responsible for over 30% of client/server performance. Some key optimizations discussed include reducing HTTP requests, optimizing response objects by reducing size and load pattern, JavaScript minification and placement, image sprites, caching, and ensuring valid HTML markup.
This document provides an overview of Google Cloud Platform (GCP) services. It discusses computing services like App Engine and Compute Engine for hosting applications. It covers storage options like Cloud Storage, Cloud Datastore and Cloud SQL. It also mentions big data services like BigQuery and machine learning services like Prediction API. The document provides brief descriptions of each service and highlights their key features. It includes code samples for using Prediction API to train a model and make predictions on new data.
This document discusses adaptive images in responsive web design. It begins by explaining why the browser should be asked about screen resolution and bandwidth instead of sniffing the browser. It then demonstrates using feature testing to determine browser width and screen resolution. Next, it covers issues with higher resolution retina displays like larger file sizes. The document proposes solutions like using .htaccess files, srcset, and JavaScript libraries to serve the appropriate image based on screen details without browser sniffing. It emphasizes that CSS media queries are still important for responsive design.
This document summarizes a presentation about Google Cloud Dataproc, a fully managed Spark and Hadoop service. It provides an overview of Dataproc's features like fast cluster provisioning, minute-based billing, and integration with other Google Cloud services. The presentation demonstrates Dataproc's pricing and performance advantages over AWS EMR, and outlines Google's roadmap to add more frameworks, tools, and data stores to Dataproc.
In this session we will present an overview from the point of view 'system that implementative on how to get the best performance from your drupal application. We will also show examples of use cases for drupal scalable infrastructure.
The web is awesome despite it's detractors. But we can't forget our fundamentals when we're trying to forge ahead with new tech. This talk is about how to approach the building blocks of the web in a way that takes advantage of their strengths and avoids their weaknesses.
Powering interactive data analysis require massive architecture, and Know-How to build a fast real-time computing system. BigQuery solves this problem by enabling super-fast, SQL-like queries against petabytes of data using the processing power of Google’s infrastructure. We will cover its core features, creating tables, columns, views, working with partitions, clustering for cost optimizations, streaming inserts, User Defined Functions, and several use cases for everydaay developer: funnel analytics, behavioral analytics, exploring unstructured data. The other part will be about BigQuery ML, which enables users to create and execute machine learning models in BigQuery using standard SQL queries. BigQuery ML democratizes machine learning by enabling SQL practitioners to build models using existing SQL tools and skills. BigQuery ML increases development speed by eliminating the need to move data.
The document discusses microservices architecture and describes how to build and deploy a sample "Hello World" application using microservices. It covers developing two projects ("World" and "Helidon_HelloWorld"), building Docker images using Cloud Build, storing artifacts in Google Cloud Storage, deploying the application to Google Kubernetes Engine, and exposing it via an external load balancer. The microservices architecture allows developing and deploying complex applications by decomposing them into independently deployable components that communicate over a network.
This document provides an overview of Django, a popular Python web framework. It discusses key features of Django including its MVT architecture, ORM, admin interface, and template system. It also covers common Django practices like project structure, apps, settings, models, views, URLs, forms, and using the Django REST framework to build APIs. Major sections include installation, configuration, building models, views, templates, and forms.
This presentation was given at the Boston Django meetup on November 16, and surveyed several leading PaaS providers including Stackato, Dotcloud, OpenShift and Heroku. For each PaaS provider, I documented the steps necessary to deploy Mezzanine, a popular Django-based CMS and blogging platform. At the end of the presentation, I do a wrap-up of the different providers and provide a comparison matrix showing which providers have which features. This matrix is likely to go out-of-date quickly because these providers are adding new features all the time.
Talk + demo given by Dipti Borkar and Roderick Yao at the Big Data Analytics Meetup #24, held in Mountain View, CA, on Nov 21st.
Invited Remote Lecture to SC21 The International Conference for High Performance Computing, Networking, Storage, and Analysis St. Louis, Missouri November 18, 2021
Solar Storms (Geo Magnetic Storms) are the motion of accelerated charged particles in the solar environment with high velocities due to the coronal mass ejection (CME).
Sustainability requires ingenuity and stewardship. Did you know Pigging Solutions pigging systems help you achieve your sustainable manufacturing goals AND provide rapid return on investment. How? Our systems recover over 99% of product in transfer piping. Recovering trapped product from transfer lines that would otherwise become flush-waste, means you can increase batch yields and eliminate flush waste. From raw materials to finished product, if you can pump it, we can pig it.
Your comprehensive guide to RPA in healthcare for 2024. Explore the benefits, use cases, and emerging trends of robotic process automation. Understand the challenges and prepare for the future of healthcare automation
Kief Morris rethinks the infrastructure code delivery lifecycle, advocating for a shift towards composable infrastructure systems. We should shift to designing around deployable components rather than code modules, use more useful levels of abstraction, and drive design and deployment from applications rather than bottom-up, monolithic architecture and delivery.
Jindong Gu, Zhen Han, Shuo Chen, Ahmad Beirami, Bailan He, Gengyuan Zhang, Ruotong Liao, Yao Qin, Volker Tresp, Philip Torr "A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models" arXiv2023 https://arxiv.org/abs/2307.12980
Support en anglais diffusé lors de l'événement 100% IA organisé dans les locaux parisiens d'Iguane Solutions, le mardi 2 juillet 2024 : - Présentation de notre plateforme IA plug and play : ses fonctionnalités avancées, telles que son interface utilisateur intuitive, son copilot puissant et des outils de monitoring performants. - REX client : Cyril Janssens, CTO d’ easybourse, partage son expérience d’utilisation de notre plateforme IA plug & play.
Recent advancements in the NIST-JARVIS infrastructure: JARVIS-Overview, JARVIS-DFT, AtomGPT, ALIGNN, JARVIS-Leaderboard
This is a powerpoint that features Microsoft Teams Devices and everything that is new including updates to its software and devices for May 2024
If you’ve ever had to analyze a map or GPS data, chances are you’ve encountered and even worked with coordinate systems. As historical data continually updates through GPS, understanding coordinate systems is increasingly crucial. However, not everyone knows why they exist or how to effectively use them for data-driven insights. During this webinar, you’ll learn exactly what coordinate systems are and how you can use FME to maintain and transform your data’s coordinate systems in an easy-to-digest way, accurately representing the geographical space that it exists within. During this webinar, you will have the chance to: - Enhance Your Understanding: Gain a clear overview of what coordinate systems are and their value - Learn Practical Applications: Why we need datams and projections, plus units between coordinate systems - Maximize with FME: Understand how FME handles coordinate systems, including a brief summary of the 3 main reprojectors - Custom Coordinate Systems: Learn how to work with FME and coordinate systems beyond what is natively supported - Look Ahead: Gain insights into where FME is headed with coordinate systems in the future Don’t miss the opportunity to improve the value you receive from your coordinate system data, ultimately allowing you to streamline your data analysis and maximize your time. See you there!
The presentation showcases the diverse real-world applications of Fused Deposition Modeling (FDM) across multiple industries: 1. **Manufacturing**: FDM is utilized in manufacturing for rapid prototyping, creating custom tools and fixtures, and producing functional end-use parts. Companies leverage its cost-effectiveness and flexibility to streamline production processes. 2. **Medical**: In the medical field, FDM is used to create patient-specific anatomical models, surgical guides, and prosthetics. Its ability to produce precise and biocompatible parts supports advancements in personalized healthcare solutions. 3. **Education**: FDM plays a crucial role in education by enabling students to learn about design and engineering through hands-on 3D printing projects. It promotes innovation and practical skill development in STEM disciplines. 4. **Science**: Researchers use FDM to prototype equipment for scientific experiments, build custom laboratory tools, and create models for visualization and testing purposes. It facilitates rapid iteration and customization in scientific endeavors. 5. **Automotive**: Automotive manufacturers employ FDM for prototyping vehicle components, tooling for assembly lines, and customized parts. It speeds up the design validation process and enhances efficiency in automotive engineering. 6. **Consumer Electronics**: FDM is utilized in consumer electronics for designing and prototyping product enclosures, casings, and internal components. It enables rapid iteration and customization to meet evolving consumer demands. 7. **Robotics**: Robotics engineers leverage FDM to prototype robot parts, create lightweight and durable components, and customize robot designs for specific applications. It supports innovation and optimization in robotic systems. 8. **Aerospace**: In aerospace, FDM is used to manufacture lightweight parts, complex geometries, and prototypes of aircraft components. It contributes to cost reduction, faster production cycles, and weight savings in aerospace engineering. 9. **Architecture**: Architects utilize FDM for creating detailed architectural models, prototypes of building components, and intricate designs. It aids in visualizing concepts, testing structural integrity, and communicating design ideas effectively. Each industry example demonstrates how FDM enhances innovation, accelerates product development, and addresses specific challenges through advanced manufacturing capabilities.