StreamSQL Feature Store (Apache Pulsar Summit)
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Input features are the building blocks for machine learning models. You cannot have a great model without great features. By building on top of Apache Pulsar's infinite retention of events, we built infrastructure to serve features in production and to generate training datasets. It allowed our machine learning teams to change, test, and deploy personalization features at an extraordinary rate to 10s of millions of end-users. This talk will discuss: - What event-sourcing is and why it's so powerful for machine learning infrastructure. - How we built the StreamSQL feature store on top of Pulsar, Flink, and Cassandra. - How a feature store accelerates ML development.
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Infrastructure Agnostic Machine Learning Workload Deployment
When it comes to Large Scale data processing and Machine Learning, Apache Spark is no doubt one of the top battle-tested frameworks out there for handling batched or streaming workloads. The ease of use, built-in Machine Learning modules, and multi-language support makes it a very attractive choice for data wonks. However bootstrapping and getting off the ground could be difficult for most teams without leveraging a Spark cluster that is already pre-provisioned and provided as a managed service in the Cloud, while this is a very attractive choice to get going, in the long run, it could be a very expensive option if it’s not well managed.
As an alternative to this approach, our team has been exploring and working a lot with running Spark and all our Machine Learning workloads and pipelines as containerized Docker packages on Kubernetes. This provides an infrastructure-agnostic abstraction layer for us, and as a result, it improves our operational efficiency and reduces our overall compute cost. Most importantly, we can easily target our Spark workload deployment to run on any major Cloud or On-prem infrastructure (with Kubernetes as the common denominator) by just modifying a few configurations.
In this talk, we will walk you through the process our team follows to make it easy for us to run a production deployment of our Machine Learning workloads and pipelines on Kubernetes which seamlessly allows us to port our implementation from a local Kubernetes set up on the laptop during development to either an On-prem or Cloud Kubernetes environment
Ml infra at an early stage
Machine Learning Infra at an early stage presented by Nick Handel at Mesosphere's Feature Store Meetup (3/5/19)
Semi-Supervised Learning In An Adversarial Environment
Unlike a typical e-commerce marketplace, Uber’s marketplace is real-time, therefore stopping fraud has to happen in real-time too. In this talk, we will dive into Account Takeover (ATO) attacks and how we built a near real-time semi-supervised learning system to keep your Uber accounts safe. ATO attacks evolve very fast and may last only for a short time period. Thus traditional way of training a model once a week/day doesn’t really help us to defend against new attack vectors. This lead us to develop a semi-supervised learning system that is built on top of Apache Spark and uses clustering techniques and feedback signals from our ATO challenges to detect and stop new attack vectors. We will discuss our results from online clustering using streaming k-means and also from batch clustering using more complex clustering algorithm, DBSCAN. We will also share some lessons on feature selection and hyperparameter tuning for clustering algorithms which plays a crucial part in performance.
Testing lightning components feb 15th 2018
Using Provar how can you keep your tests robust when migrating from the Classic UI, and how can you use Provar to test Aura custom lightning components and flexipages?
Professionalizing the Front-end
This presentation is all about : why do we need Front-end developers, how do they work and what techniques, tools, languages and frameworks they are using on daily basis.
# Do you work so hard that you don’t have time to catch up with all the new front-end trends?
# Are you pondering to hire a front-end developer but you are still unsure if it is worth?
# Do you think it is about time to leave the full-stack development and focus in the front-end?
During presentation I will try to answer all those questions giving a complete overview on how Front-end apps are being developed. I will talk about : workflows, automated processes, Linting & styling, SASS, Unit and E2E testing, TDD, Hot reload, JS typed libraries, UI component libraries, UI frameworks and much more.
Strata parallel m-ml-ops_sept_2017
Machine Learning in Production
The era of big data generation is upon us. Devices ranging from sensors to robots and sophisticated applications are generating increasing amounts of rich data (time series, text, images, sound, video, etc.). For such data to benefit a business’s bottom line, insights must be extracted, a process that increasingly requires machine learning (ML) and deep learning (DL) approaches deployed in production applications use cases.
Production ML is complicated by several challenges, including the need for two very distinct skill sets (operations and data science) to collaborate, the inherent complexity and uniqueness of ML itself, when compared to other apps, and the varied array of analytic engines that need to be combined for a practical deployment, often across physically distributed infrastructure. Nisha Talagala shares solutions and techniques for effectively managing machine learning and deep learning in production with popular analytic engines such as Apache Spark, TensorFlow, and Apache Flink.
Design Patterns In Scala
A design pattern is a general repeatable solution to a commonly occurring problem in software design. They make your code scalable, robust and easy for developers to learn. The three categories - Creational, Structural and Behavioral. A major look through of the Scala specific design patterns such as the Lens pattern, duck typing, memoization, etc. These patterns let you explore the features of Scala and use a design pattern using those features which can help you solve your different use cases.
Seamless MLOps with Seldon and MLflow
Deploying and managing machine learning models at scale introduces new complexities. Fortunately, there are tools that simplify this process. In this talk we walk you through an end-to-end hands on example showing how you can go from research to production without much complexity by leveraging the Seldon Core and MLflow frameworks. We will train a set of ML models, and we will showcase a simple way to deploy them to a Kubernetes cluster through sophisticated deployment methods, including canary deployments, shadow deployments and we’ll touch upon richer ML graphs such as explainer deployments.
MLflow: Infrastructure for a Complete Machine Learning Life Cycle with Mani ...
ML development brings many new complexities beyond the traditional software development lifecycle. Unlike in traditional software development, ML developers want to try multiple algorithms, tools, and parameters to get the best results, and they need to track this information to reproduce work. In addition, developers need to use many distinct systems to productionize models. To address these problems, many companies are building custom “ML platforms” that automate this lifecycle, but even these platforms are limited to a few supported algorithms and to each company’s internal infrastructure. In this session, we introduce MLflow, a new open source project from Databricks that aims to design an open ML platform where organizations can use any ML library and development tool of their choice to reliably build and share ML applications. MLflow introduces simple abstractions to package reproducible projects, track results, and encapsulate models that can be used with many existing tools, accelerating the ML lifecycle for organizations of any size. In this deep-dive session, through a complete ML model life-cycle example, you will walk away with:
MLflow concepts and abstractions for models, experiments, and projects
How to get started with MLFlow
Understand aspects of MLflow APIs
Using tracking APIs during model training
Using MLflow UI to visually compare and contrast experimental runs with different tuning parameters and evaluate metrics
Package, save, and deploy an MLflow model
Serve it using MLflow REST API
What’s next and how to contribute
Javantura v4 - FreeMarker in Spring web - Marin Kalapać
Javantura v4 - FreeMarker in Spring web - Marin KalapaćHUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association
Javantura v4 - FreeMarker in Spring web - Marin KalapaćRsqrd AI: ML Tooling at an AI-first Startup
n this talk, Rsqrd welcomes Emad Elwany, CTO and Co-Founder of Lexion! He discusses his experiences with ML tooling and how it has evolved through the lifespan of Lexion, and shares his findings on important considerations, problems and solutions, and how decisions about ML tooling have changed over time through the stages of a startup.
**These slides are from a talk given at Rsqrd AI. Learn more at rsqrdai.org**
Joomla Modules with Permissions and Front-End Editing
Imaging a Joomla website where staff can edit modules on the front-end. Randy Carey of the iCue Project presents his work on making this a reality and on the issues he discovered during implementation of the solution. This presentation was given at JAB 2013 near Amsterdam.
What's New in IBM Java 8 SE?
Java SE 8 is the latest eagerly anticipated release of the Java platform that powers much of IBM's software and provides functionality for you to get your work done. This presentation describes the new features available in the virtual machine and associated libraries and tooling. Learn how to be more productive as a developer, use new techniques for exploiting modern hardware to process large volumes of data in parallel with GPUs, move data efficiently across the network, and exploit the virtualization potential of your data center. The talk outlines a road map for IBM's technology and valuable tips directly from IBM's Java engineers.
Foundations for Scaling ML in Apache Spark by Joseph Bradley at BigMine16
Apache Spark has become the most active open source Big Data project, and its Machine Learning library MLlib has seen rapid growth in usage. A critical aspect of MLlib and Spark is the ability to scale: the same code used on a laptop can scale to 100’s or 1000’s of machines. This talk will describe ongoing and future efforts to make MLlib even faster and more scalable by integrating with two key initiatives in Spark. The first is Catalyst, the query optimizer underlying DataFrames and Datasets. The second is Tungsten, the project for approaching bare-metal speeds in Spark via memory management, cache-awareness, and code generation. This talk will discuss the goals, the challenges, and the benefits for MLlib users and developers. More generally, we will reflect on the importance of integrating ML with the many other aspects of big data analysis.
About MLlib: MLlib is a general Machine Learning library providing many ML algorithms, feature transformers, and tools for model tuning and building workflows. The library benefits from integration with the rest of Apache Spark (SQL, streaming, Graph, core), which facilitates ETL, streaming, and deployment. It is used in both ad hoc analysis and production deployments throughout academia and industry.
Foundations for Scaling ML in Apache Spark
Apache Spark has become the most active open source Big Data project, and its Machine Learning library MLlib has seen rapid growth in usage. A critical aspect of MLlib and Spark is the ability to scale: the same code used on a laptop can scale to 100’s or 1000’s of machines. This talk will describe ongoing and future efforts to make MLlib even faster and more scalable by integrating with two key initiatives in Spark. The first is Catalyst, the query optimizer underlying DataFrames and Datasets. The second is Tungsten, the project for approaching bare-metal speeds in Spark via memory management, cache-awareness, and code generation. This talk will discuss the goals, the challenges, and the benefits for MLlib users and developers. More generally, we will reflect on the importance of integrating ML with the many other aspects of big data analysis.
Similar to StreamSQL Feature Store (Apache Pulsar Summit) (20)
ML Platform Q1 Meetup: Airbnb's End-to-End Machine Learning Infrastructure
ML Platform Q1 Meetup: Airbnb's End-to-End Machine Learning Infrastructure
Tech leaders guide to effective building of machine learning products
Tech leaders guide to effective building of machine learning products
Infrastructure Agnostic Machine Learning Workload Deployment
Infrastructure Agnostic Machine Learning Workload Deployment
Semi-Supervised Learning In An Adversarial Environment
Semi-Supervised Learning In An Adversarial Environment
MLflow: Infrastructure for a Complete Machine Learning Life Cycle with Mani ...
MLflow: Infrastructure for a Complete Machine Learning Life Cycle with Mani ...
Javantura v4 - FreeMarker in Spring web - Marin Kalapać
Javantura v4 - FreeMarker in Spring web - Marin Kalapać
Joomla Modules with Permissions and Front-End Editing
Joomla Modules with Permissions and Front-End Editing
Foundations for Scaling ML in Apache Spark by Joseph Bradley at BigMine16
Foundations for Scaling ML in Apache Spark by Joseph Bradley at BigMine16
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Empowering Data Analytics Ecosystem.pptx
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
原版定制【微信:41543339】【(BCU毕业证书)伯明翰城市大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
原版定制【微信:41543339】【(Adelaide毕业证书)阿德莱德大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
一比一原版(QU毕业证)皇后大学毕业证成绩单
QU毕业证【微信95270640】办理皇后大学毕业证原版一模一样、QU毕业证制作【Q微信95270640】《皇后大学毕业证购买流程》《QU成绩单制作》皇后大学毕业证书QU毕业证文凭皇后大学
本科毕业证书,学历学位认证如何办理【留学国外学位学历认证、毕业证、成绩单、大学Offer、雅思托福代考、语言证书、学生卡、高仿教育部认证等一切高仿或者真实可查认证服务】代办国外（海外）英国、加拿大、美国、新西兰、澳大利亚、新西兰等国外各大学毕业证、文凭学历证书、成绩单、学历学位认证真实可查。
1:1完美还原海外各大学毕业材料上的工艺：水印阴影底纹钢印LOGO烫金烫银LOGO烫金烫银复合重叠。文字图案浮雕激光镭射紫外荧光温感复印防伪。
可办理以下真实皇后大学存档留学生信息存档认证：
1皇后大学真实留信网认证（网上可查永久存档无风险百分百成功入库）；
2真实教育部认证（留服）等一切高仿或者真实可查认证服务（暂时不可办理）；
3购买英美真实学籍（不用正常就读直接出学历）；
4英美一年硕士保毕业证项目（保录取学校挂名不用正常就读保毕业）
留学本科/硕士毕业证书成绩单制作流程：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询皇后大学皇后大学硕士毕业证成绩单）；
2开始安排制作皇后大学毕业证成绩单电子图；
3皇后大学毕业证成绩单电子版做好以后发送给您确认；
4皇后大学毕业证成绩单电子版您确认信息无误之后安排制作成品；
5皇后大学成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）
— — — — — — — — — — — 《文凭顾问Q/微：95270640》很感动很无奈房东的儿子小伍笨手笨脚的不会说普通话满口粤语态度十分傲慢一副盛气凌人的样子山娃试图接近他跟他交友与城里人交友但他俩就好像是两个世界里的人根本拢不到一块儿不知不觉山娃倒跟周围出租屋里的几个小伙伴成了好朋友因为他们也是从乡下进城过暑假的小学生快乐的日子总是过得飞快山娃尚未完全认清那几位小朋友时他们却一个接一个地回家了山娃这时才恍然发现二个月的暑假已转到了尽头他的城市生活也将划上一个不很圆义
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
一比一原版(Deakin毕业证书)迪肯大学毕业证如何办理
原版定制【微信:41543339】【(Deakin毕业证书)迪肯大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
原版定制【微信:41543339】【(UniSA毕业证书)南澳大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
Adjusting primitives for graph : SHORT REPORT / NOTES
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
UIUC毕业证offer【微信95270640】☀《伊利诺伊大学|厄巴纳-香槟分校毕业证购买》GoogleQ微信95270640《UIUC毕业证模板办理》加拿大文凭、本科、硕士、研究生学历都可以做,二、业务范围：
★、全套服务：毕业证、成绩单、化学专业毕业证书伪造《伊利诺伊大学|厄巴纳-香槟分校大学毕业证》Q微信95270640《UIUC学位证书购买》
(诚招代理)办理国外高校毕业证成绩单文凭学位证,真实使馆公证（留学回国人员证明）真实留信网认证国外学历学位认证雅思代考国外学校代申请名校保录开请假条改GPA改成绩ID卡
1.高仿业务:【本科硕士】毕业证,成绩单（GPA修改）,学历认证（教育部认证）,大学Offer,,ID,留信认证,使馆认证,雅思,语言证书等高仿类证书；
2.认证服务: 学历认证（教育部认证）,大使馆认证（回国人员证明）,留信认证（可查有编号证书）,大学保录取,雅思保分成绩单。
3.技术服务：钢印水印烫金激光防伪凹凸版设计印刷激凸温感光标底纹镭射速度快。
办理伊利诺伊大学|厄巴纳-香槟分校伊利诺伊大学|厄巴纳-香槟分校毕业证offer流程：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）
-办理真实使馆公证（即留学回国人员证明）
-办理各国各大学文凭（世界名校一对一专业服务,可全程监控跟踪进度）
-全套服务：毕业证成绩单真实使馆公证真实教育部认证。让您回国发展信心十足！
（详情请加一下 文凭顾问+微信:95270640）欢迎咨询！的鬼地方父亲的家在高楼最底屋最下面很矮很黑是很不显眼的地下室父亲的家安在别人脚底下须绕过高楼旁边的垃圾堆下八个台阶才到父亲的家很狭小除了一张单人床和一张小方桌几乎没有多余的空间山娃一下子就联想起学校的男小便处山娃很想笑却怎么也笑不出来山娃很迷惑父亲的家除了一扇小铁门连窗户也没有墓穴一般阴森森有些骇人父亲的城也便成了山娃的城父亲的家也便成了山娃的家父亲让山娃呆在屋里做作业看电视最多只能在门口透透气间
一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
毕业原版【微信:41543339】【(Coventry毕业证书)考文垂大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(YU毕业证)约克大学毕业证成绩单
YU毕业证【微信95270640】（约克大学毕业证高仿学位证书((+《Q微信95270640》))）购买YU毕业证修改YU成绩单购买约克大学毕业证办YU文凭办高仿毕业证约克大学毕业证购买修改成绩单挂科退学如何进行学历认证留学退学办毕业证书/ 出国留学无法毕业买毕业证留学被劝退买毕业证（非正常毕业教育部认证咨询） York University
办理国外约克大学毕业证书 #成绩单改成绩 #教育部学历学位认证 #毕业证认证 #留服认证 #使馆认证（留学回国人员证明） #（证）等
真实教育部认证教育部存档中国教育部留学服务中心认证（即教育部留服认证）网站100%可查.
真实使馆认证（即留学人员回国证明）使馆存档可通过大使馆查询确认.
留信网认证国家专业人才认证中心颁发入库证书留信网永久存档可查.
约克大学约克大学毕业证学历书毕业证 #成绩单等全套材料从防伪到印刷从水印到钢印烫金跟学校原版100%相同.
国际留学归国服务中心：实体公司注册经营行业标杆精益求精！
国外毕业证学位证成绩单办理流程：
1客户提供办理约克大学约克大学毕业证学历书信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）；
2开始安排制作约克大学毕业证成绩单电子图；
3约克大学毕业证成绩单电子版做好以后发送给您确认；
4约克大学毕业证成绩单电子版您确认信息无误之后安排制作成品；
5约克大学成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快递邮寄约克大学约克大学毕业证学历书）。心温柔地对待我将渐渐老去的父母体谅他们以反哺之心奉敬父母以感恩之心孝顺父母哪怕只为父母换洗衣服为父母喂饭送汤按摩酸痛的腰背握着父母的手扶着他们一步一步地慢慢散步.让我们的父母幸福快乐地度过一生挽着清风芒耀似金的骄阳如将之绽放的花蕾一般静静的从远方的山峦间缓缓升起这一片寂静的城市默默的等待着它的第一缕光芒将之唤醒那飘散在它前方的几层薄云像是新娘的婚纱一般为它的光芒添上了几分淡淡的浮晕在悄无声息间这怕
一比一原版(CBU毕业证)卡普顿大学毕业证成绩单
CBU毕业证【微信95270640】☀《卡普顿大学毕业证购买》GoogleQ微信95270640《CBU毕业证模板办理》加拿大文凭、本科、硕士、研究生学历都可以做,二、业务范围：
★、全套服务：毕业证、成绩单、化学专业毕业证书伪造《卡普顿大学大学毕业证》Q微信95270640《CBU学位证书购买》
专业为留学生办理卡普顿大学卡普顿大学本科毕业证成绩单【100%存档可查】留学全套申请材料办理。本公司承诺所有毕业证成绩单成品全部按照学校原版工艺对照一比一制作和学校一样的羊皮纸张保证您证书的质量！
如果你回国在学历认证方面有以下难题请联系我们我们将竭诚为你解决认证瓶颈
1所有材料真实但资料不全无法提供完全齐整的原件。【如：成绩单丶毕业证丶回国证明等材料中有遗失的。】
2获得真实的国外最终学历学位但国外本科学历就读经历存在问题或缺陷。【如：国外本科是教育部不承认的或者是联合办学项目教育部没有备案的或者外本科没有正常毕业的。】
3学分转移联合办学等情况复杂不知道怎么整理材料的。时间紧迫自己不清楚递交流程的。
如果你是以上情况之一请联系我们我们将在第一时间内给你免费咨询相关信息。我们将帮助你整理认证所需的各种材料.帮你解决国外学历认证难题。
国外卡普顿大学卡普顿大学本科毕业证成绩单办理方法：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询卡普顿大学卡普顿大学本科毕业证成绩单）；
2开始安排制作卡普顿大学毕业证成绩单电子图；
3卡普顿大学毕业证成绩单电子版做好以后发送给您确认；
4卡普顿大学毕业证成绩单电子版您确认信息无误之后安排制作成品；
5卡普顿大学成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。父亲太伟大了居然能单匹马地跑到这么远这么大这么美的地方赚大钱高楼大厦鳞次栉比大街小巷人潮涌动山娃一路张望一路惊叹他发现城里的桥居然层层叠叠扭来扭去桥下没水却有着水一般的车水马龙山娃惊诧于城里的公交车那么大那么美不用买票乖乖地掷下二枚硬币空调享受还能坐着看电视呢屡经辗转山娃终于跟着父亲到家了山娃没想到父亲城里的家会如此寒碜更没料到父亲的城里竟有如此简陋的鬼地方父亲的家在高楼最底屋最下面很矮很黑是子
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
学校原件一模一样【微信：741003700 】《(Deakin毕业证书)迪肯大学毕业证学位证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
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三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
一比一原版(BU毕业证)波士顿大学毕业证成绩单
BU毕业证【微信95270640】购买（波士顿大学毕业证成绩单硕士学历）Q微信95270640代办BU学历认证留信网伪造波士顿大学学位证书精仿波士顿大学本科/硕士文凭证书补办波士顿大学 diplomaoffer,Transcript购买波士顿大学毕业证成绩单购买BU假毕业证学位证书购买伪造波士顿大学文凭证书学位证书,专业办理雅思、托福成绩单，学生ID卡，在读证明，海外各大学offer录取通知书，毕业证书，成绩单，文凭等材料:1:1完美还原毕业证、offer录取通知书、学生卡等各种在读或毕业材料的防伪工艺（包括 烫金、烫银、钢印、底纹、凹凸版、水印、防伪光标、热敏防伪、文字图案浮雕，激光镭射，紫外荧光，温感光标）学校原版上有的工艺我们一样不会少，不论是老版本还是最新版本，都能保证最高程度还原，力争完美以求让所有同学都能享受到完美的品质服务。
专业为留学生办理波士顿大学波士顿大学毕业证offer【100%存档可查】留学全套申请材料办理。本公司承诺所有毕业证成绩单成品全部按照学校原版工艺对照一比一制作和学校一样的羊皮纸张保证您证书的质量！
如果你回国在学历认证方面有以下难题请联系我们我们将竭诚为你解决认证瓶颈
1所有材料真实但资料不全无法提供完全齐整的原件。【如：成绩单丶毕业证丶回国证明等材料中有遗失的。】
2获得真实的国外最终学历学位但国外本科学历就读经历存在问题或缺陷。【如：国外本科是教育部不承认的或者是联合办学项目教育部没有备案的或者外本科没有正常毕业的。】
3学分转移联合办学等情况复杂不知道怎么整理材料的。时间紧迫自己不清楚递交流程的。
如果你是以上情况之一请联系我们我们将在第一时间内给你免费咨询相关信息。我们将帮助你整理认证所需的各种材料.帮你解决国外学历认证难题。
国外波士顿大学波士顿大学毕业证offer办理方法：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询波士顿大学波士顿大学毕业证offer）；
2开始安排制作波士顿大学毕业证成绩单电子图；
3波士顿大学毕业证成绩单电子版做好以后发送给您确认；
4波士顿大学毕业证成绩单电子版您确认信息无误之后安排制作成品；
5波士顿大学成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。二条巴掌般大的裤衩衩走出泳池山娃感觉透身粘粘乎乎散发着药水味有点痒山娃顿时留恋起家乡的小河潺潺活水清凉无比日子就这样孤寂而快乐地过着寂寞之余山娃最神往最开心就是晚上无论多晚多累父亲总要携山娃出去兜风逛夜市流光溢彩人潮涌动的都市夜生活总让山娃目不暇接惊叹不已父亲老问山娃想买什么想吃什么山娃知道父亲赚钱很辛苦除了书籍和文具山娃啥也不要能牵着父亲的手满城闲逛他已心满意足了父亲连挑了三套童装叫山娃试穿山伸
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StreamSQL Feature Store (Apache Pulsar Summit)
- 1. Feature Stores Building ML Infrastructure on Apache Pulsar
- 2. Simba Khadder Co-Founder & CEO StreamSQL.io Using Apache Pulsar to power our feature store for >100m MAU
- 3. Agenda ● The ML process ● Moving our ML Pipelines w/ Pulsar ● Building a Feature Store on top of Pulsar ● Q&A
- 4. Last 5 articles read Current article Top Genre Average Content Length Diversity of reading tastes .... Recommend Next Article Input Features Model Output Machine Learning :: Model(Features) = Output
- 5. Feature Engineering > Model Research*
- 6. Last 5 articles read Current article Top Category Total time spent reading Diversity of reading tastes .... Recommend Next Article Input Features Model Output Behind every great model is a set of great features
- 8. Credit: Microsoft Azure Sales deck
- 9. Our ML teams spent >80% of their time building and maintaining ML pipelines for feature generation and feature engineering.
- 10. Deploy Feature to Production Validate New Feature Increases Performance Generate Training Dataset with new Feature Hypothesis New Feature The Feature Engineering Cycle
- 11. Training Data Online Features Serving Train User ID Feature Set Arr([FeatureSet, Actual])
- 12. Last 5 articles read Current article Top Category Total time spent reading Diversity of reading tastes .... Recommend Next Article Input Features Model Output
- 13. Generating Point-in-Time Correct Training Data Time read Features at timestamp read Features at timestamp read Features at timestamp Events Storage Training Data
- 14. Generating Features for Serving (in a perfect world) Time read Features at timestamp read Features at timestamp read Features at timestamp Event Stream Online FeaturesProcessor
- 15. Last 5 articles read Current article Top Category Total time spent reading Diversity of reading tastes .... Recommend Next Article Input Features Model Output Most Features are Stateful
- 16. Total time spent reading Input Features Model Output Stateful Features must be Bootstrapped
- 17. Bootstrapping Stateful Features with Historical Data in S3 SELECT user, SUM(readtime) FROM read_events GROUP BY user;
- 18. Time Persisted in S3 Not in S3, but in Kafka retention period MsgID
- 19. Finish bootstrapping & start stream processing from Kafka SELECT user, SUM(readtime) FROM read_events GROUP BY user;
- 20. Full Feature Deployment Process
- 22. Combine Batch & Stream Processing with an Immutable Ledger ● Each new event appends to the end of the ledger ● Cut at an arbitrary point, and the ledger looks like a batch problem ● Only read from the head of the ledger and it looks like streaming problem
- 23. Pulsar Based Architecture with Infinite Retention
- 24. Pulsar’s offloading makes Event-Sourcing achievable
- 25. Pulsar’s Tiered Architecture enhances Processing on Infinite Retention
- 26. Feature are the building blocks of ML models; however, they are developed and maintained in ad-hoc ways. They lack a dedicated system of management.
- 27. ML Pipelines < Feature Stores ● No concrete feature definitions, feature logic is split across Flink jobs. ● No feature versioning and rollback. ● No feature sharing, re-use, and discovery. ● No integrations into Tensorflow, Jupyter, etc.
- 28. A Platform for features allows for teams to work together. Features are easily defined, shared, and re-used. There exists a single source of truth for features.
- 29. Last 5 articles read Current article Top Category Total time spent reading Diversity of reading tastes .... Recommend Next Article Input Features Model Output Models across an organization may benefit from some of these features.
- 30. StreamSQL.io accelerates and enhances machine learning development ● Facilitate model development Discover, re-use, and share features across teams and models. ● Deploy with confidence Use a single feature definition for training and serving. ● Limit complexity Unified streaming and batch processing for feature generation. ● Increase model performance Use 3rd party features from text embeddings to weather data.
- 32. 1. Connect and Upload Data
- 33. 2. Transform and Join Data
- 34. 3. Define and Serve Features
- 35. 4. Generate Training Data
- 37. Deploy Feature to Production Validate New Feature Increases Performance Generate Training Dataset with new Feature Hypothesis New Feature The Feature Engineering Cycle
- 38. StreamSQL The Feature Store for Machine Learning Beta