Microsoft bot framework
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The document discusses the Microsoft Bot Framework, which provides tools for building and connecting intelligent bots that interact with users across various services. It describes bots and chatbots, then explains that the Bot Framework allows bots to be built that can interact through text, SMS, Skype, Slack, Office 365 mail and other popular services. It also outlines the development process for building bots using the Bot Framework, including registering bots, using dialogs and state, and integrating LUIS for natural language understanding. Resources for further learning about the Bot Framework are also listed.
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- Examples of where deep learning is used including speech recognition, image recognition, and natural language processing.
- Descriptions of common deep learning architectures like convolutional neural networks and recurrent neural networks.
- An overview of popular deep learning libraries including Caffe, Torch, Theano, and TensorFlow.
- A demonstration of building and training a simple deep learning model in Keras.
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Progressive Web AppsSoftware Infrastructure Progressive Web Apps (PWAs) are web applications that use modern web capabilities to deliver native app-like experiences to users. PWAs work across platforms and can be installed by users. They are built using service workers, web app manifests, and other modern web technologies. PWAs provide fast loading, engage users with new features like push notifications, and offer an app-like user experience without limiting users to a single platform.
Java9
Java9Software Infrastructure This document discusses Java 9 and its new module system. The main features of Java 9 include the Java Platform Module System (JPMS) which provides strong encapsulation and improves security and reliability. It also introduces a new modular structure for the Java SE platform. The document provides an overview of modules, automatic modules, and how to migrate existing applications to use the new module system.
Machine learning
Machine learningSoftware Infrastructure This document provides an overview of machine learning fundamentals and techniques. It defines machine learning as a field that allows computers to learn without being explicitly programmed. It also describes supervised learning techniques like regression and classification and unsupervised learning techniques like clustering. Specific algorithms discussed include linear regression, logistic regression, neural networks, K-means clustering, and anomaly detection. Frameworks for machine learning like Azure ML and Spark MLlib are also summarized.
Raspberry PI
Raspberry PISoftware Infrastructure The document discusses the Raspberry Pi, a small, inexpensive computer that can run various operating systems like Raspbian, Arch Linux, and Windows 10 IoT Core. It has 40 GPIO pins that allow users to connect external circuits and boards to control them using code. Example projects built with Raspberry Pi are described, such as a home media server, baby monitor, network-wide ad blocker, customized picture frame, automated pet feeder, and more.
Golang
GolangSoftware Infrastructure GoLang is an open source programming language created by Google in 2009. It has a large community and was designed for scalability and concurrency. Some key features include being statically typed, compiled, and having built-in support for concurrency through goroutines and channels. Google uses GoLang extensively to build systems that scale to thousands of machines.
Codename one
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Hazelcast sunumSoftware Infrastructure Hazelcast is an open source in-memory data grid based on Java. It provides distributed map, set, queue, topic, and lock data structures that allow for data to be stored in memory and partitioned across a cluster of nodes. Clients can interact with the data structures without needing to know the details of the cluster setup. Hazelcast is used by many companies for caching, computing, and messaging workloads. It has both open source and paid enterprise editions that provide additional features like WAN replication and security.
Blockchain use cases
Blockchain use casesSoftware Infrastructure The document provides an overview of blockchain use cases. It begins with remembering the key components of blockchain like blocks, miners, proof of work, and distributed ledgers. It then discusses public versus private blockchains and how private blockchains allow for control over participants. Several specific use cases are outlined, including smart contracts, proof of existence services, digital notarization of photos/videos, digital weddings, lottery systems, alarm clock apps, and banking operating systems. It is suggested that 2017 will be a year when more blockchain proofs of concept and pilots move into limited production and early adoption.
The Fintechs
The FintechsSoftware Infrastructure This document discusses fintechs and provides definitions and examples. It begins by defining fintech as the use of technology to make financial systems more efficient. It then discusses what fintechs do, including providing services like lending, payments and money transfers in a more convenient way than traditional banks. The document provides examples of fintech applications and companies. It also discusses topics like open banking, APIs, fintech adoption rates in different parts of the world, and the fintech ecosystem in Turkey.
Server Side Swift
Server Side SwiftSoftware Infrastructure This document discusses server-side Swift, including:
- An overview of the history and growth of programming languages from the 1940s to today.
- Features of the Swift programming language like variables, optionals, and closures.
- Tools for server-side Swift development like the Swift Package Manager.
- Benefits of using Swift for server applications like performance, safety, and Apple support.
- Popular web frameworks for Swift including Perfect, Vapor, and Kitura.
- Benchmarking server applications written in Swift.
Push Notification
Push NotificationSoftware Infrastructure Push notifications allow software applications to deliver messages and notifications to users without requiring the user to actively check for updates. Push notifications can contain data, notifications, or both. There are two main platforms for delivering push notifications: Firebase Cloud Messaging (FCM) for Android and Apple Push Notification Service (APNs) for iOS. Both support delivering notifications via HTTP and XMPP/MQTT protocols. iOS 10 introduced enhancements like rich notifications that allow images, videos, and interactive buttons in notifications. It also introduced notification extensions that give developers more control over customizing notification content.
.Net Core
.Net CoreSoftware Infrastructure .NET Core is an open source development platform maintained by Microsoft that allows developers to write cross-platform applications using C# and F# that run on Windows, Linux, and macOS. It is not based on .NET Framework or Mono, but is compatible with apps and libraries that target the .NET Standard Library. .NET Core focuses on cloud development and does not support all features of .NET Framework like Windows Forms. ASP.NET Core is also cross-platform and uses a modular package-based approach rather than depending on System.Web.dll. The .NET Core roadmap includes adding support for more platforms and features like WebSockets and SignalR in upcoming releases.
Java Batch
Java BatchSoftware Infrastructure The document discusses Java Batch (JSR-352), which specifies an application programming model for batch processing. It provides common requirements like logging, checkpointing, and transaction management. JSR-352 defines a job specification language and Java programming model. It describes batch job, step, and application concepts. The specification targets Java SE and EE platforms and requires Java 6 or higher. It works with dependency injection containers.
Big Data & Hadoop
Big Data & HadoopSoftware Infrastructure - Hadoop is a leading big data platform that uses distributed storage and computation to scale linearly using the Hadoop Distributed File System and MapReduce framework.
- The Hadoop ecosystem includes components like HDFS, Apache Kafka, Apache Flume, and Apache Spark.
- Sample analysis of data collected on October 7th and 17th from 32 JVMs showed transaction volumes and data sizes ranging from hundreds of gigabytes to terabytes.
- Analysis showed durations and distributions of transactions across different services, with most time spent in external systems and a few key services.
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- 2. What is a Bot ? A "software robot device" or software agent. Especially an intelligent agent
- 3. What is a chat Bot ? A computer program designed to simulate conversation with human users, especially over the Internet. Usage?
- 4. What is Microsoft Bot Framework? Provides just what you need to build and connect intelligent bots that interact naturally wherever your users are talking, from text/sms to Skype, Slack, Office 365 mail and other popular services.
- 5. Development https://dev.botframework.com/ Template Simulator Registering Bot () MicrosoftAppId MicrosoftAppPassword
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- 11. Resources GitHub/ KubilayKara/BotDemo YouTube/ Building a Conversational Bot: From 0 to 60 YouTube/ Intelligent Labs YouTube/ Creating a Facebook and a Skype Bot using the Microsoft Bot Framework Gary Pretty/ Building conversational forms with FormFlow and Microsoft Bot Framework David Zientara/ Got Bot? Building A Conversational UX With the Bot Framework Microsoft Developer/ What is Microsoft Bot Framework Overview
- 12. Soru ve Cevaplar
- 13. Teşekkürler