Slides from PyData Berlin, July 2017 meetup
Plotly Dash is a newest addition to a rich ecosystem of tools to build visual data science and BI applications in Python.
Plotly is an online analytics and visualization tool with open-source Python and JavaScript libraries. The libraries allow users to create interactive charts in Python scripts, Jupyter notebooks, and web applications. The offline feature allows exporting charts without using the Plotly platform. Charts can be created in Jupyter notebooks and exported to local HTML files or used in web apps by defining the chart on the server and rendering it client-side using JSON.
Introduction to Dash framework from Plotly, reactive framework for building dashboards in Python. Tech talk covers basics and more advanced topics like custom component and scaling.
Speaker: Damian Rodziewicz.
Resources:
1. Blogpost
https://appsilon.com/overview-of-dash-python-framework-from-plotly-for-building-dashboards/
2. Github
https://github.com/DamianRodziewicz/dash_example
app.py
https://github.com/DamianRodziewicz/dash_example longer_computations_app.py
3. Youtube:
https://youtu.be/NUXUmv-aeG4
This presentation provides an overview of interactive data visualization using the Dash-Plotly libraries. It discusses the need for data visualization in presentations, reports, machine learning and real-time data. It contrasts static versus interactive graphs and how Dash allows for changing views and updating graphs automatically from multiple sources. An overview of the Plotly and Dash libraries is given, including the basic components of graphs, figures, data and layout. Examples of interactive graphs and dashboards using these libraries will be provided.
Collaborative environment with data science notebook Moon Soo Lee
This document discusses how to build an efficient data science toolchain around notebook technologies. It describes how notebooks can be used for interactive analytics and collaboration. It recommends sharing notebooks and data to maximize their potential. Methods for sharing include GitHub, nbviewer, Apache Zeppelin, and commercial services. It also discusses enabling multi-user environments through JupyterHub and Zeppelin and building data catalogs for managing and sharing datasets.
Bokeh is an interactive Python visualization library that targets modern web browsers for presentation. It aims to provide elegant and concise construction of novel graphics in D3.js style, with high-performance interactivity over large or streaming datasets. Bokeh can help create interactive plots, dashboards, and data applications. It outputs JSON files that serve as input for the BokehJS JavaScript library. While it has bindings for other languages, this discussion will focus on Bokeh's Python capabilities, which include basic and advanced charting features. Bokeh can also display plots from libraries like Matplotlib, Seaborn, and ggplot.
Slides from PyData Berlin, July 2017 meetup
Plotly Dash is a newest addition to a rich ecosystem of tools to build visual data science and BI applications in Python.
Plotly is an online analytics and visualization tool with open-source Python and JavaScript libraries. The libraries allow users to create interactive charts in Python scripts, Jupyter notebooks, and web applications. The offline feature allows exporting charts without using the Plotly platform. Charts can be created in Jupyter notebooks and exported to local HTML files or used in web apps by defining the chart on the server and rendering it client-side using JSON.
Introduction to Dash framework from Plotly, reactive framework for building dashboards in Python. Tech talk covers basics and more advanced topics like custom component and scaling.
Speaker: Damian Rodziewicz.
Resources:
1. Blogpost
https://appsilon.com/overview-of-dash-python-framework-from-plotly-for-building-dashboards/
2. Github
https://github.com/DamianRodziewicz/dash_example
app.py
https://github.com/DamianRodziewicz/dash_example longer_computations_app.py
3. Youtube:
https://youtu.be/NUXUmv-aeG4
This presentation provides an overview of interactive data visualization using the Dash-Plotly libraries. It discusses the need for data visualization in presentations, reports, machine learning and real-time data. It contrasts static versus interactive graphs and how Dash allows for changing views and updating graphs automatically from multiple sources. An overview of the Plotly and Dash libraries is given, including the basic components of graphs, figures, data and layout. Examples of interactive graphs and dashboards using these libraries will be provided.
Collaborative environment with data science notebook Moon Soo Lee
This document discusses how to build an efficient data science toolchain around notebook technologies. It describes how notebooks can be used for interactive analytics and collaboration. It recommends sharing notebooks and data to maximize their potential. Methods for sharing include GitHub, nbviewer, Apache Zeppelin, and commercial services. It also discusses enabling multi-user environments through JupyterHub and Zeppelin and building data catalogs for managing and sharing datasets.
Bokeh is an interactive Python visualization library that targets modern web browsers for presentation. It aims to provide elegant and concise construction of novel graphics in D3.js style, with high-performance interactivity over large or streaming datasets. Bokeh can help create interactive plots, dashboards, and data applications. It outputs JSON files that serve as input for the BokehJS JavaScript library. While it has bindings for other languages, this discussion will focus on Bokeh's Python capabilities, which include basic and advanced charting features. Bokeh can also display plots from libraries like Matplotlib, Seaborn, and ggplot.
The document discusses GraphQL, Relay, and some of their benefits and challenges. Some key points covered include:
- GraphQL allows for declarative and UI-driven data fetching which can optimize network requests.
- Relay uses GraphQL and allows defining data requirements and composing queries to fetch nested data in one roundtrip.
- Benefits include simpler API versioning since fields can be changed without breaking clients.
- Challenges include verbose code, lack of documentation, and not supporting subscriptions or local state management out of the box.
- Overall GraphQL aims to solve many data fetching problems but has a complex setup process and learning curve.
Eugene Poltorakov.HTML 5 and drupal.DrupalCamp Kiev 2011camp_drupal_ua
Eugene Poltorakov will give a presentation on HTML5, discussing what's new in HTML5, why developers should use it, and where and how it can be used. The presentation will cover new form elements, structure elements, block level elements, media elements, and attributes introduced in HTML5. It will also discuss new APIs such as Canvas, Drag&Drop, offline storage, and media playback. The presentation will provide links for further information on HTML5 specifications from WHATWG and W3C, as well as cross-browser polyfills.
This document provides an overview of Kotlin backend development with a focus on GraphQL and REST APIs. Key points include:
- The author has over 10 years of experience with functional reactive full stack development using Kotlin.
- GraphQL is introduced as an API format developed by Facebook that is strongly typed, self-documenting, and allows clients to specify the data they need in one request.
- Frameworks like Apollo and additional libraries can expand GraphQL's capabilities by adding features like caching, monitoring, and schema stitching.
- The author focuses on using Apollo for its support across platforms like Kotlin, JavaScript, iOS, and Android. Reasons for choosing Apollo include its wide backend support
This document provides an overview of HTML and HTML5, including:
- It acknowledges that HTML can seem nonsensical and inconsistent at first glance.
- It lists several new APIs that have been added to HTML5, such as Server-Sent Events, Local Storage, Audio, Video, Canvas 2D, and more.
- It shows the relationships between various groups involved in developing HTML, including the HTML WG, WHAT WG, and W3C.
- It poses questions about how job roles related to web development may have changed from 2004 to present, with the rise of HTML5.
This document discusses GraphQL, a query language for APIs and a runtime for fulfilling queries with existing data. It provides examples of basic queries, nested fields, connections, arguments, and fragments. It also covers GraphQL types including scalars, schemas, definitions, predicates, and data resolution. GraphQL allows clients to define the structure of the data required, and specifies querying, modifying, and transmitting data between client and server.
Google Cloud Data Fusion is a managed service that allows users to visually build and run data pipelines without coding. It converts the graphical pipeline design into a directed acyclic graph (DAG) to run batch or streaming jobs on an ephemeral Dataproc cluster. The presenter demoed building a sample pipeline using the drag and drop interface and explored the tool's monitoring and logging capabilities. While the tool aims to save labor hours, its beta limitations include slow instance creation, lack of input validation, and Java stacktraces in errors. Pricing is based on hourly development costs and Dataproc execution costs.
This document provides an overview of flow-based programming (FBP). FBP is a programming paradigm where applications are defined as networks of black box processes that exchange data through predefined connections. These connections can be redefined without changing the internal processes, allowing for endless reconfiguration. FBP was invented in the 1960s and has seen a resurgence of interest with tools like NoFlo that allow building distributed applications as connected processes. The document discusses several open source FBP implementations and frameworks and provides examples of how FBP has been used to build applications and bioinformatics libraries.
Despite the “Graph” in the name, GraphQL is mostly used to query relational databases or object models. But it is really well suited to querying graph databases too. In this talk, I’ll demonstrate how I implemented a GraphQL endpoint for the Neo4j graph database and how you would use it in your app.
Join Joseph Sirosh, Corporate Vice President of the Cloud AI Platform, for a deep dive into the AI platform and exciting AI use cases. Joseph will showcase how every developer can infuse intelligence into their applications and create amazing new experiences with AI. In this exciting overview, you will learn about the application of AI technologies in the cloud. We will help you understand how to add pre-built AI capabilities like object detection, face understanding, translation and speech to applications. We will show how developers can build Cognitive Search applications that understand deep content in images, text and other data. We will also show how the platform can be used to build your own custom AI models for predictive applications and how to use the Azure platform to accelerate machine learning. Joseph will also show how companies assemble end-to-end systems of intelligence using the rich variety of data and application development services on Azure.
A Social network and Learning Centre is designed to help users to meet new friends, maintain existing relationships and at the same time enhance their concepts related to Java. The main goal of our website is to make your social life more active and stimulating. This project helps you to connect People, share your ideas and enhance your Programming Concepts related to Java, Android & Windows .
In this project a new class of resource available where you can Read, Write, Compile and Run Java Program with webface Online Compiler. Lecture Notes Available With Example. Your Personal Image, Music & Video Gallery, That makes Complete Platform For Everyone.
• Language Used : JSP & Servlet.
• Designing : Html, CSS, JavaScript
• IDE : NetBeans 8.0.2
• Database : MySQL 5.1.
# Complete project report Made By abhishek Kumar
conTEXT -- Lightweight Text Analytics using Linked DataAli Khalili
The Web democratized publishing -- everybody can easily publish information on a Website, Blog, in social networks or microblogging systems. The more the amount of published information grows, the more important are technologies for accessing, analysing, summarising and visualising information. While substantial progress has been made in the last years in each of these areas individually, we argue, that only the intelligent combination of approaches will make this progress truly useful and leverage further synergies between techniques. In this paper we develop a text analytics architecture of participation, which allows ordinary people to use sophisticated NLP techniques for analysing and visualizing their content, be it a Blog, Twitter feed, Website or article collection. The architecture comprises interfaces for information access, natural language processing and visualization. Dierent exchangeable components can be plugged into this architecture, making it easy to tailor for individual needs. We evaluate the usefulness of our approach by comparing both the eectiveness and eciency of end users within a task-solving setting. Moreover, we evaluate the usability of our approach using a questionnaire-driven approach. Both evaluations suggest that oridinary Web users are empowered to analyse their data and perform tasks, which were previously out of reach.
ESPC Teams week Microsoft Teams & Bot Framework – a Developer’s PerspectiveThomas Gölles
The document discusses Microsoft Teams and the Bot Framework from a developer's perspective. It provides an overview of the Teams platform and capabilities for building bots and tabs. Key points include:
- The Teams platform allows for building organizational apps, partner apps, and custom apps using tabs, bots, and other features.
- The Bot Framework SDK supports building bots in C#, JavaScript, Python and Java. Bots can integrate with Teams and other channels.
- Features like tabs, actions, and task modules allow embedding rich content and collecting user input within Teams.
- A demo will showcase using the Bot Framework to build a bot and integrating it with Teams.
PyData London Bokeh Tutorial - Bryan Van de VenPyData
This document provides information about Bokeh, an interactive visualization library for Python that allows creating browser-based visualizations. It describes Bokeh's capabilities like interactive glyphs that link visual elements to data, high-level expressions for interactivity, and outputting plots to the web. The document also outlines upcoming features and provides links to download materials, videos, and code repositories to learn more about Bokeh and data visualization.
Creative Interactive Browser Visualizations with Bokeh by Bryan Van de venPyData
Bokeh is an interactive visualization library for Python that allows creating browser-based plots, dashboards, and data applications. It produces static or live interactive visualizations for large datasets. Key features include high-level abstractions, interactive tools, linking views, streaming data support, and integration with Jupyter notebooks. The developer is seeking feedback to improve usability and expand capabilities like abstract rendering for millions of data points.
Session about types of analytics. Descriptive, diagnostic, predictive and prescriptive analytics.
Conference DATA ANALYSIS DEVELOPMENT 2016 by RZECZPOSPOLITA.
This document discusses modernizing applications and APIs to the cloud using Microsoft Azure. It provides an overview of Azure services that can help with application modernization including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), containers, serverless computing, and support for all stages of application modernization from lift-and-shift to cloud native. It also discusses how Azure provides choice, flexibility, and powerful capabilities including support for any programming language or framework.
The Larch - a visual interactive programming environmentPython Ireland
The Larch Environment is a visual interactive programming environment for Jython/Python, that makes programming more visual. Its is designed for the creation of visual interactive programs, and programs that operate as interactive technical literature. To this end, protocols for presenting objects visually have been devised. An active document based programming environment builds on the edit-run-debug cycle of a standard console, allowing a programmer to experiment with ideas, and develop visual programs at the same time. Additionally, a way of embellishing source code with visual content is presented.
http://sites.google.com/site/larchenv
Building a Real-Time IoT monitoring application with AzureDavide Mauri
Being able to analyze data in real-time is a very hot topic already and it will be more and more in. From product recommendations to fraud detection alarms a lot of stuff would be perfect if it could happen in real time. In this session a sample solution using the serverless capabilities of Azure will be developed, right from the ingestion of sensor data to their analysis and recommendation using AI in real time. Come to see how you could do the same in your environment, moving your application capabilities to the next level.
The document discusses GraphQL, Relay, and some of their benefits and challenges. Some key points covered include:
- GraphQL allows for declarative and UI-driven data fetching which can optimize network requests.
- Relay uses GraphQL and allows defining data requirements and composing queries to fetch nested data in one roundtrip.
- Benefits include simpler API versioning since fields can be changed without breaking clients.
- Challenges include verbose code, lack of documentation, and not supporting subscriptions or local state management out of the box.
- Overall GraphQL aims to solve many data fetching problems but has a complex setup process and learning curve.
Eugene Poltorakov.HTML 5 and drupal.DrupalCamp Kiev 2011camp_drupal_ua
Eugene Poltorakov will give a presentation on HTML5, discussing what's new in HTML5, why developers should use it, and where and how it can be used. The presentation will cover new form elements, structure elements, block level elements, media elements, and attributes introduced in HTML5. It will also discuss new APIs such as Canvas, Drag&Drop, offline storage, and media playback. The presentation will provide links for further information on HTML5 specifications from WHATWG and W3C, as well as cross-browser polyfills.
This document provides an overview of Kotlin backend development with a focus on GraphQL and REST APIs. Key points include:
- The author has over 10 years of experience with functional reactive full stack development using Kotlin.
- GraphQL is introduced as an API format developed by Facebook that is strongly typed, self-documenting, and allows clients to specify the data they need in one request.
- Frameworks like Apollo and additional libraries can expand GraphQL's capabilities by adding features like caching, monitoring, and schema stitching.
- The author focuses on using Apollo for its support across platforms like Kotlin, JavaScript, iOS, and Android. Reasons for choosing Apollo include its wide backend support
This document provides an overview of HTML and HTML5, including:
- It acknowledges that HTML can seem nonsensical and inconsistent at first glance.
- It lists several new APIs that have been added to HTML5, such as Server-Sent Events, Local Storage, Audio, Video, Canvas 2D, and more.
- It shows the relationships between various groups involved in developing HTML, including the HTML WG, WHAT WG, and W3C.
- It poses questions about how job roles related to web development may have changed from 2004 to present, with the rise of HTML5.
This document discusses GraphQL, a query language for APIs and a runtime for fulfilling queries with existing data. It provides examples of basic queries, nested fields, connections, arguments, and fragments. It also covers GraphQL types including scalars, schemas, definitions, predicates, and data resolution. GraphQL allows clients to define the structure of the data required, and specifies querying, modifying, and transmitting data between client and server.
Google Cloud Data Fusion is a managed service that allows users to visually build and run data pipelines without coding. It converts the graphical pipeline design into a directed acyclic graph (DAG) to run batch or streaming jobs on an ephemeral Dataproc cluster. The presenter demoed building a sample pipeline using the drag and drop interface and explored the tool's monitoring and logging capabilities. While the tool aims to save labor hours, its beta limitations include slow instance creation, lack of input validation, and Java stacktraces in errors. Pricing is based on hourly development costs and Dataproc execution costs.
This document provides an overview of flow-based programming (FBP). FBP is a programming paradigm where applications are defined as networks of black box processes that exchange data through predefined connections. These connections can be redefined without changing the internal processes, allowing for endless reconfiguration. FBP was invented in the 1960s and has seen a resurgence of interest with tools like NoFlo that allow building distributed applications as connected processes. The document discusses several open source FBP implementations and frameworks and provides examples of how FBP has been used to build applications and bioinformatics libraries.
Despite the “Graph” in the name, GraphQL is mostly used to query relational databases or object models. But it is really well suited to querying graph databases too. In this talk, I’ll demonstrate how I implemented a GraphQL endpoint for the Neo4j graph database and how you would use it in your app.
Join Joseph Sirosh, Corporate Vice President of the Cloud AI Platform, for a deep dive into the AI platform and exciting AI use cases. Joseph will showcase how every developer can infuse intelligence into their applications and create amazing new experiences with AI. In this exciting overview, you will learn about the application of AI technologies in the cloud. We will help you understand how to add pre-built AI capabilities like object detection, face understanding, translation and speech to applications. We will show how developers can build Cognitive Search applications that understand deep content in images, text and other data. We will also show how the platform can be used to build your own custom AI models for predictive applications and how to use the Azure platform to accelerate machine learning. Joseph will also show how companies assemble end-to-end systems of intelligence using the rich variety of data and application development services on Azure.
A Social network and Learning Centre is designed to help users to meet new friends, maintain existing relationships and at the same time enhance their concepts related to Java. The main goal of our website is to make your social life more active and stimulating. This project helps you to connect People, share your ideas and enhance your Programming Concepts related to Java, Android & Windows .
In this project a new class of resource available where you can Read, Write, Compile and Run Java Program with webface Online Compiler. Lecture Notes Available With Example. Your Personal Image, Music & Video Gallery, That makes Complete Platform For Everyone.
• Language Used : JSP & Servlet.
• Designing : Html, CSS, JavaScript
• IDE : NetBeans 8.0.2
• Database : MySQL 5.1.
# Complete project report Made By abhishek Kumar
conTEXT -- Lightweight Text Analytics using Linked DataAli Khalili
The Web democratized publishing -- everybody can easily publish information on a Website, Blog, in social networks or microblogging systems. The more the amount of published information grows, the more important are technologies for accessing, analysing, summarising and visualising information. While substantial progress has been made in the last years in each of these areas individually, we argue, that only the intelligent combination of approaches will make this progress truly useful and leverage further synergies between techniques. In this paper we develop a text analytics architecture of participation, which allows ordinary people to use sophisticated NLP techniques for analysing and visualizing their content, be it a Blog, Twitter feed, Website or article collection. The architecture comprises interfaces for information access, natural language processing and visualization. Dierent exchangeable components can be plugged into this architecture, making it easy to tailor for individual needs. We evaluate the usefulness of our approach by comparing both the eectiveness and eciency of end users within a task-solving setting. Moreover, we evaluate the usability of our approach using a questionnaire-driven approach. Both evaluations suggest that oridinary Web users are empowered to analyse their data and perform tasks, which were previously out of reach.
ESPC Teams week Microsoft Teams & Bot Framework – a Developer’s PerspectiveThomas Gölles
The document discusses Microsoft Teams and the Bot Framework from a developer's perspective. It provides an overview of the Teams platform and capabilities for building bots and tabs. Key points include:
- The Teams platform allows for building organizational apps, partner apps, and custom apps using tabs, bots, and other features.
- The Bot Framework SDK supports building bots in C#, JavaScript, Python and Java. Bots can integrate with Teams and other channels.
- Features like tabs, actions, and task modules allow embedding rich content and collecting user input within Teams.
- A demo will showcase using the Bot Framework to build a bot and integrating it with Teams.
PyData London Bokeh Tutorial - Bryan Van de VenPyData
This document provides information about Bokeh, an interactive visualization library for Python that allows creating browser-based visualizations. It describes Bokeh's capabilities like interactive glyphs that link visual elements to data, high-level expressions for interactivity, and outputting plots to the web. The document also outlines upcoming features and provides links to download materials, videos, and code repositories to learn more about Bokeh and data visualization.
Creative Interactive Browser Visualizations with Bokeh by Bryan Van de venPyData
Bokeh is an interactive visualization library for Python that allows creating browser-based plots, dashboards, and data applications. It produces static or live interactive visualizations for large datasets. Key features include high-level abstractions, interactive tools, linking views, streaming data support, and integration with Jupyter notebooks. The developer is seeking feedback to improve usability and expand capabilities like abstract rendering for millions of data points.
Session about types of analytics. Descriptive, diagnostic, predictive and prescriptive analytics.
Conference DATA ANALYSIS DEVELOPMENT 2016 by RZECZPOSPOLITA.
This document discusses modernizing applications and APIs to the cloud using Microsoft Azure. It provides an overview of Azure services that can help with application modernization including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), containers, serverless computing, and support for all stages of application modernization from lift-and-shift to cloud native. It also discusses how Azure provides choice, flexibility, and powerful capabilities including support for any programming language or framework.
The Larch - a visual interactive programming environmentPython Ireland
The Larch Environment is a visual interactive programming environment for Jython/Python, that makes programming more visual. Its is designed for the creation of visual interactive programs, and programs that operate as interactive technical literature. To this end, protocols for presenting objects visually have been devised. An active document based programming environment builds on the edit-run-debug cycle of a standard console, allowing a programmer to experiment with ideas, and develop visual programs at the same time. Additionally, a way of embellishing source code with visual content is presented.
http://sites.google.com/site/larchenv
Building a Real-Time IoT monitoring application with AzureDavide Mauri
Being able to analyze data in real-time is a very hot topic already and it will be more and more in. From product recommendations to fraud detection alarms a lot of stuff would be perfect if it could happen in real time. In this session a sample solution using the serverless capabilities of Azure will be developed, right from the ingestion of sensor data to their analysis and recommendation using AI in real time. Come to see how you could do the same in your environment, moving your application capabilities to the next level.
Azure Meetup: Novità CosmosDB modalità Serverless e Cognitive Servicesdotnetcode
The document discusses new features of Azure Cosmos DB, a multi-model database service. It begins with an introduction to NoSQL databases and how they originated. It then outlines three new key features of Cosmos DB: 1) serverless capabilities that allow customers to pay based on consumption, 2) built-in Jupyter notebooks for interactive querying and visualization, and 3) integration of notebooks with GitHub. The document concludes with a demo of how these features can be used together with other Azure services like Cognitive Search, Computer Vision, and Functions.
Nuxeo Semantic ECM: from Scribo and Stanbol to valuable applicationsNuxeo
Work on integrating semantic technologies developed in several R&D projects is now progressing at full speed. Expect to see creative new uses of semantic technologies in Nuxeo open source content management products in 2011!
Now you know how to get up and running with a SharePoint Framework project, how to get up and running with Microsoft Graph and use it in your SharePoint Framework solutions we will look at integrating with Microsoft Teams.
Join this session to understand available assets of SharePoint Framework (SPFx) and what is important for you as SharePoint Developer and Architect in the development area with SharePoint modern portals. In this session, you will know more about extending existing experiences across SharePoint and Teams.
RIC 2.0 is the next version of the Research Information Centre platform, building on lessons learned from RIC 1.0. Key features of RIC 2.0 include integrated scientific workflows through Project Trident, data deposit and sharing capabilities through Zentity, and enhanced authoring and data analysis tools in Microsoft Office. RIC 2.0 aims to provide researchers a collaborative environment for managing the entire research lifecycle within a customizable platform available in various deployment options.
This document outlines the Trivadis Integration Architecture Blueprint, which provides an approach for structuring, designing, and understanding integration in application landscapes. It defines four layers - process, mediation, collection/distribution, and communication - to model integration at the architecture level. The blueprint has evolved over several years based on experience with many integration projects. It aims to provide a vendor-neutral methodology for integration modeling. The document also provides examples of how common integration scenarios can be depicted using the blueprint layers and discusses how various integration platforms map to the blueprint.
Microsoft Teams - A developers perspectiveThomas Gölles
Microsoft Teams is a chat-based collaboration platform that allows users to communicate through chat, audio/video calls, and collaboration on Office 365 files and apps. It provides enterprise-level security and manageability. Third-party apps can be integrated to customize Teams and extend its functionality. The document discusses how apps can optimize teamwork in Teams through tabs, bots, and other extensions. It also demonstrates some example apps built for Teams.
This document discusses reusable pieces in Logic Apps and Azure Functions integration. It announces an upcoming Integration Monday webinar on using BizTalk with Logic Apps and Azure Functions. The presenter then demonstrates how to easily create reusable logic app workflows by calling nested logic apps from within the designer. Users are encouraged to provide feedback and suggestions to help improve Logic Apps.
This document provides an overview of the SharePoint Framework and its capabilities for building client-side web parts and extensions. It discusses how web parts can raise and subscribe to events using the SharePoint Framework's centralized event aggregation service. It also outlines the different types of extensions that are available like application customizers, command set customizers, and field customizers which allow customizing specific areas, commands, and fields in SharePoint. The document concludes by mentioning upcoming areas of development for the SharePoint Framework.
Real NET Docs Show - Serverless Machine Learning v3.pptxLuis Beltran
Slides of my presentation about Serverless Machine Learning using Azure Functions, Twilio APIs, and Cognitive Services for text and image processing of WhatsApp messages at .NET Docs Show weekly community event organized by Microsoft
This document summarizes a presentation on explaining machine learning models with Python. It discusses different interpretable machine learning techniques like LIME, SHAP, anchors, and surrogate models that can be used to explain "black box" models. It provides code demos of using techniques like permutation feature importance, partial dependence plots, and model debugging with ELI5 in Python. The goal is to help data scientists understand and explain their machine learning models.
This document provides an overview of Apache Spark, including:
1) A brief history of Spark and description of its core components for batch processing, streaming, SQL queries, machine learning and graph processing.
2) Benefits of Spark such as performance, developer productivity, ecosystem support, and a unified engine.
3) Explanations of what makes Spark fast, including in-memory computing and caching of remote data locally.
4) A link to learn more about Databricks, a company that provides a cloud-based analytics platform with Spark.
This document provides links to various resources related to machine learning including Azure machine learning services, an overview of Microsoft's machine learning portfolio, a deep learning virtual machine review, demo links, and links to Kaggle competitions and notebooks on topics like word embeddings and recurrent neural networks. It also includes contact information for the author.
This document discusses PyData, a meetup group for data science. It provides reasons to join PyData like its community and for learning machine learning software. It also includes links to Kaggle competitions and tutorials related to toxicity analysis and natural language processing. The document advertises Microsoft's machine learning and AI products and when each may be suitable. It ends by promoting upcoming meetup events and linking to tutorials on deep learning techniques like GRUs, LSTMs and word embeddings.
The document summarizes the agenda for the first PyData meetup organized by Andrey Vykhodtsev. The meetup will include short introductions to Pandas and NumPy, a comparison of SQL and Pandas, an interactive demo of Pandas features like data loading, indexing, grouping and plotting. Attendees will learn why Pandas and NumPy are core tools in the Python data science toolchain and how numerous libraries build upon them.
This document provides an overview of installing Apache Hadoop and Spark from scratch. It discusses prerequisites like servers, operating systems, and Hadoop distributions. Key Hadoop components like YARN, HDFS, MapReduce and Ambari are introduced. Apache Spark is summarized as a fast, general-purpose cluster computing system. The installation process is walked through, including using Ambari to deploy Hadoop services across master and slave nodes. Additional steps like adding nodes, automation with Ansible, and zero-installation options are also covered.
The document provides an overview of Spark and notebooks for data science. It discusses:
- The data science workflow and tools needed including Spark, notebooks, and libraries
- How notebooks provide an interactive environment for data scientists to do work like literate programming, reproducibility, and code with descriptions
- Spark is introduced as an in-memory compute engine that works with large data volumes for highly iterative analysis at scale
- Popular notebook servers like Jupyter, Zeppelin, and others are presented along with how to install and use them with Spark
- Languages like Python, R, and Scala are demonstrated for use in notebooks along with libraries for tasks like machine learning, data analysis, and visualization.
Apache Spark is a fast, general-purpose, and easy-to-use cluster computing system for large-scale data processing. It provides APIs in Scala, Java, Python, and R. Spark is versatile and can run on YARN/HDFS, standalone, or Mesos. It leverages in-memory computing to be faster than Hadoop MapReduce. Resilient Distributed Datasets (RDDs) are Spark's abstraction for distributed data. RDDs support transformations like map and filter, which are lazily evaluated, and actions like count and collect, which trigger computation. Caching RDDs in memory improves performance of subsequent jobs on the same data.
Big Data Essentials meetup @ IBM Ljubljana 23.06.2015Andrey Vykhodtsev
The document discusses big data concepts and Hadoop technologies. It provides an overview of massive parallel processing and the Hadoop architecture. It describes common processing engines like MapReduce, Spark, Hive, Pig and BigSQL. It also discusses Hadoop distributions from Hortonworks, Cloudera and IBM along with stream processing and advanced analytics on Hadoop platforms.
This document summarizes IBM's major commitment to advance Apache Spark. It announces that IBM will build Spark into the core of its analytics and commerce platforms. Key aspects of IBM's commitment include contributing its SystemML machine learning system to Spark, educating 1 million data professionals on Spark, and establishing a Spark Technology Center to inspire Spark adoption and contribute to its development. The document provides background on what Spark is and why IBM is making this commitment.
Digital Banking in the Cloud: How Citizens Bank Unlocked Their MainframePrecisely
Inconsistent user experience and siloed data, high costs, and changing customer expectations – Citizens Bank was experiencing these challenges while it was attempting to deliver a superior digital banking experience for its clients. Its core banking applications run on the mainframe and Citizens was using legacy utilities to get the critical mainframe data to feed customer-facing channels, like call centers, web, and mobile. Ultimately, this led to higher operating costs (MIPS), delayed response times, and longer time to market.
Ever-changing customer expectations demand more modern digital experiences, and the bank needed to find a solution that could provide real-time data to its customer channels with low latency and operating costs. Join this session to learn how Citizens is leveraging Precisely to replicate mainframe data to its customer channels and deliver on their “modern digital bank” experiences.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...Alex Pruden
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...
20170927 py data_n3_bokeh_plotly
1. Part 1: Interactive visualisations
Andrey Vykhodtsev anvykhod@Microsoft.com
Cloud Solution Architect, Data & AI
PyDataLjubljanaMeetup#3
2. Agenda
Welcome to PyData meetup #3!
This group is sponsored by PyData &
NumFocus
Snacks and venue are provided by
Agenda
Part 1: Interactive visualisations with
Bokeh, Plotly, Dash and Flask (30-40
min)
Part 2: Automation and measurements
with Python (30-40 min)
3. Agenda(part1)
Bokeh hands-on overview
What is bokeh
Main structures
Data Sources
Applications
Plotly & Dash
Quick intro to Plotly and Dash
Examples and demos
Embedding your visualizations into Flask
applications
Publishing your Flask apps to Azure App Services
4. WhatisBokeh
Python library for building rich interactive
visualizations
Translated to JS (BokehJS)
Can be embedded into a web app or distributed
standalone