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Weaving patterns with artificial intelligence, Part 3: Using Markov Chains to generate language from letter correlation matrices and N-grams
Now that you have learned how to compile statistics of letter correlation and word correlation in model natural language text, put it to work having the computer generate text of its own. Learn how to write programs that create sequences of letters or words based on randomly generated transitions to complete N-grams.
Articles 07 May 2018
Convolutional neural networks
Learn about convolutional neural networks (CNN) and see how to use Python to implement a simple network that classifies handwritten digits.
Articles 02 May 2018
A hybrid approach to integrating Watson Assistant into an existing site
Hybrid search is a new way to use IBM Watson Assistant without some of the limitations of a traditional chatbot. This approach lets you have best of both worlds: a robust search engine, which is coupled with AI technology that is capable of evolving as Watson receives additional training over time.
Articles 01 May 2018
Weaving patterns with artificial intelligence, Part 2: Word analysis and N-grams in a variety of practical applications
Build on the concept of N-grams of sequential letters to look at N-grams of words, and the statistics that can be derived from these. Learn how to generate graphical plots of N-gram frequencies. Explore the American National Corpus as an enormous and rich source of English text suitable for general-purpose language modeling tasks.
Also available in: Chinese  
Articles 18 Apr 2018
Create a natural language classifier that identifies spam
Watson Natural Language Classifier is part of the IBM Watson cognitive services platform on IBM Cloud. In this article, you'll use Watson Natural Language Classifier on IBM Cloud to create, train, and test the accuracy of a spam classification service.
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Articles 16 Apr 2018
Analyzing the contextual content of hierarchical data by using IBM Watson Explorer
This tutorial demonstrates how to implement a custom crawler plug-in with IBM Watson Explorer to analyze a hierarchical data structure within the context of content analytics. The strategy outlined here permits the retaining of the hierarchical structure or grains of the model being analyzed.
Also available in: Chinese  
Articles 08 Apr 2018
Weaving patterns with artificial intelligence, Part 1: Letter correlation and simple language statistics for AI
AI is more than pattern recognition. It can also build on patterns to generate expression. This is increasingly important in the world of intelligent agents. Learn about generative AI, an important class of techniques to the modern developer. As a first step, consider the patterns in natural language and how these can be modeled to prepare machines to generate their own expressions of familiar language. Discover how to go from basic letter frequency statistics to correlation between letters by using matrix-based models.
Also available in: Chinese  
Articles 20 Mar 2018
Minecraft and IBM Cloud, Part 4: Integrating Watson into Minecraft on IBM Cloud
In this tutorial series, you'll learn how to use Docker, Eclipse, and IBM Cloud to develop, extend, and host your own Minecraft servers. Find out how to use Eclipse to build Minecraft plugins, test them locally using Docker, and use IBM Cloud to host your Docker containers on the Internet. You'll also harness the power of IBM Watson from within Minecraft for more educational and interactive game play. In Part 4, you'll learn how to extend the Spigot server with a plugin that uses Watson cognitive services to add a little science to your game play.
Also available in: Chinese   Japanese  
Articles 19 Mar 2018
Port a business chatbot to Watson Assistant
Follow along as a member of the Watson Applied Research team explains how they helped a client improve their chatbot by using Watson Conversation.
Also available in: Chinese  
Articles 16 Mar 2018
Build a cognitive IoT app in just 7 steps
Build a cognitive IoT solution, following an edge computing architecture. Push your analytics out to the gateway, and use advanced machine learning to detect anomalies.
Also available in: Chinese   Japanese  
Tutorial 14 Mar 2018
Build a chatbot in the IBM Cloud
If you're looking to get started with chatbots, Watson services in IBM Cloud make it easy. In this tutorial, you'll learn both basic and advanced techniques for building chatbots that respond intelligently to your users.
Also available in: Chinese  
Articles 04 Mar 2018
Developing cognitive IoT solutions for anomaly detection by using deep learning, Part 5: Using Keras and TensorFlow for anomaly detection
This article is the fifth in a five-part series, "Developing cognitive IoT solutions for anomaly detection by using deep learning." This article demonstrates a deep learning solution using Keras and TensorFlow and how it is used to analyze the large amount of data that IoT sensors gather.
Also available in: Chinese  
Tutorial 02 Mar 2018
Supervised learning models
Examine the theory and ideas behind supervised learning and its application in exploring data and data sets and calculating probability.
Also available in: Chinese  
Articles 26 Feb 2018
Build cognitive solutions for industries, Part 4: Enhancing the simplicity and quality of human-computer interactions
Cognitive computing is becoming increasingly important within the enterprise. In this fourth tutorial in a series, we discuss the primary methodologies and patterns used to build cognitive solutions for the telecommunications and media and entertainment industries.
Also available in: Chinese  
Articles 21 Feb 2018
Design for cognitive experiences, Part 1: The human-to-machine communication model
Discover better insights with higher confidence faster than humanly possible. It is the key to taking a first step in the right cognitive application direction: asking not what could it do but what it should do. With artificial intelligence (AI), we have decades of data and research into human thought processes and communication to use a blueprint. To simulate human relationships, we begin by observing and better understanding ourselves.
Also available in: Chinese  
Articles 29 Jan 2018
Get to know your deep learning frameworks, Part 2: Get started with PyTorch
Originally developed as a Python wrapper for the LuaJIT-based Torch framework, PyTorch, now a native Python package, redesigns and implements Torch in Python while sharing the same core C libraries for the back-end code. Get to know PyTorch.
Also available in: Chinese  
Articles 18 Jan 2018
Cleansing, processing, and visualizing a data set, Part 3: Visualizing data
In this tutorial, discover some of the more useful applications for visualizing data and a few of the approaches you can use to create that visualization, including the R programming language, gnuplot, and Graphviz.
Also available in: Chinese  
Articles 17 Jan 2018
IoT Lessons Learned: Lessons learned while building a closed-loop, full-stack cognitive IoT application
In this lessons learned article, discover how this lifetime hacker hacked together emerging IoT and cognitive technologies to create a proof-of-concept for an age-in-place healthcare scenario. The lessons included: cognitive IoT apps must be learning systems; context defines success; and you don't always know what you don't know.
Also available in: Chinese  
Articles 15 Jan 2018
Create an artificial neural network using the Neuroph Java framework
Build an artificial neural network (ANN) using the Java language and Neuroph open source framework.
Also available in: Chinese  
Articles 08 Jan 2018
Get to know your deep learning frameworks, Part 1: Get started with Keras
This article gives you a quick overview of Keras, a Python-based, deep-learning library. Learn about the framework's benefits, supported platforms, installation considerations, and supported back ends.
Also available in: Chinese  
Articles 18 Dec 2017
Get to know your deep learning frameworks, Part 3: Get started with Deeplearning4j
Eclipse Deeplearning4j (DL4j) is a framework of deep learning tools and libraries that take advantage of the Java Virtual Machine, making it easier to deploy deep learning in enterprise big data applications.
Also available in: Chinese  
Articles 18 Dec 2017
Migrating from Watson Retrieve and Rank to Discovery, Part 2: Add your data to Watson Discovery
The first part of this series introduced how to migrate from Watson Retrieve and Rank to Watson Discovery service using original source data. In this part, we'll look at how to migrate applications by taking data directly from Watson Retrieve and Rank and adding it to Watson Discovery.
Also available in: Chinese  
Articles 12 Dec 2017
Adapt DevOps to cognitive and artificial intelligence systems
Explore an outline of a "cognitive DevOps" process that refines and adapts the best parts of DevOps for new cognitive or artificial intelligence applications. Specifically, the tutorial covers applying DevOps to the training process of cognitive systems including training data, modeling, and performance evaluation.
Articles 12 Dec 2017
Models for machine learning
Take a dive into the algorithms used in machine learning. Learn about supervised, unsupervised, and reinforcement learning, as well as the models that make them work.
Also available in: Chinese  
Articles 05 Dec 2017
Think Big with Decision Composer on IBM Cloud
Learn step-by-step how to deploy a Decision Composer application to the Business Rules service and run it within Hadoop. Access IBM Cloud Lite free.
Articles 05 Dec 2017
Unsupervised learning for data classification
Discover the theory and ideas behind unsupervised learning and its possible application in exploring data and data sets.
Also available in: Chinese  
Articles 04 Dec 2017
Think Big with Decision Composer on IBM Cloud
Learn step-by-step how to deploy a Decision Composer application to the Business Rules service and run it within Hadoop. Access IBM Cloud Lite free.
Also available in: Chinese   Japanese  
Articles 04 Dec 2017
Build a cognitive alert system for your IT operations
Learn how to integrate IT service management with AI services on an IoT device. You'll build a cognitive alert system for your IT operations.
Also available in: Chinese  
Tutorial 24 Nov 2017
Developing cognitive IoT solutions for anomaly detection by using deep learning, Part 4: Using Apache SystemML for anomaly detection
This article is the fourth in a five-part series, "Developing cognitive IoT solutions for anomaly detection by using deep learning." This article demonstrates a deep learning solution using Apache SystemML and how it is used to analyze the large amount of data that IoT sensors gather.
Also available in: Chinese  
Tutorial 22 Nov 2017
Analyzing IoT device movement data
This tutorial builds upon the "Create a fun, simple IoT accelerometer game" tutorial. It shows how to capture 3 different types of movement data (instead of just 1), it shows how to send that data to the IBM Cloud using IBM Watson IoT Platform, and finally it shows how to analyze that data with the Watson Machine Learning service and SPSS Modeler.
Tutorial 21 Nov 2017
Get to know your deep learning frameworks, Part 4: Getting started with TensorFlow
TensorFlow is just one of the many open source software libraries for machine learning. In this tutorial, get an overview of TensorFlow, learn which platforms support it, and look at installation considerations.
Also available in: Chinese  
Articles 16 Nov 2017
Train a software agent to behave rationally with reinforcement learning
Learn about reinforcement learning, a subfield of machine learning with which you can train software agents to behave rationally in an environment. In this article, you'll delve into the technology and discover some of the problem areas to which you can apply it.
Also available in: Chinese   Portuguese   Spanish  
Articles 11 Oct 2017
Migrating from Watson Retrieve and Rank to Discovery, Part 1: Migrating from Watson Retrieve and Rank to Watson Discovery Service
This tutorial guides you through the process of creating and training a Watson Discovery Service with sample data. This tutorial uses the same data set used in the Retrieve and Rank "Getting Started Tutorial" but you can use the same approach to create a service instance that uses your own data.
Also available in: Chinese  
Articles 03 Oct 2017
Big-brained data, Part 2: Apply the software development lifecycle to the data that feeds AI applications
Apply the iterative software development lifecycle (SDLC) to data for artificial intelligence (AI) and cognitive applications. Improve your systems for sourcing and assessment of data sets, and controlling dimensionality, all the way through the evaluation that feeds each iteration in the cycle.
Also available in: Chinese   Portuguese   Spanish  
Articles 02 Oct 2017
Big-brained data, Part 1: Pay attention to the data to get the most out of artificial intelligence, machine learning, and cognitive computing
Gain a sound understanding of the crucial role of data in the development of artificial intelligence and cognitive applications, and how this importance has developed throughout the history of AI, though not always explicitly acknowledged. Learn how the quality and quantity of available data can make all the difference in pattern analysis and training. AI is experiencing a resurgence on the web, but the understanding that a good data corpus is the lifeblood of any AI is not widespread. Learn to avoid the enormous danger from AI doing more harm than good if problems of bias and statistical skew propagate from the data corpus. Gain an edge in developing successful AI applications by understanding the role of data in various AI techniques, and the characteristics of data sets that support those techniques.
Also available in: Chinese   Japanese   Portuguese   Spanish  
Articles 27 Sep 2017
Minecraft and IBM Cloud, Part 3: Running Spigot servers in Kubernetes
In this tutorial series, you'll learn how to use Docker, Eclipse, and IBM Cloud to develop, extend, and host your own Minecraft servers. Find out how to use Eclipse to build Minecraft plugins, test them locally using Docker, and use IBM Cloud to host your Docker containers on the Internet. You'll also harness the power of IBM Watson from within Minecraft for more educational and interactive game play. In Part 3, you learn how to take the plugin that you built in Part 2 to the next level -- by getting it running on the web in IBM Cloud.
Also available in: Chinese   Japanese  
Articles 20 Sep 2017
The languages of AI
From a self-learning checkers game to IBM Watson playing Jeopardy!, artificial intelligence (AI) has been an intense focus of computer research. Learn more about the history of AI and the languages that have advanced its use and capabilities.
Also available in: Chinese   Japanese   Portuguese   Spanish  
Articles 18 Sep 2017
Monitor mobile devices with the Geospatial Analytics service
Obtain, run, and extend a Node.js starter application that uses the IBM Cloud Geospatial Analytics service. With the Geospatial Analytics service, you can monitor moving devices from the Internet of Things. The service analyzes a device message stream from MQTT and tracks device locations in real time with respect to one or more geographic regions.
Also available in: Chinese   Russian   Japanese  
Articles 11 Sep 2017
Deep learning architectures
Discover the range and types of deep learning neural architectures and networks, including RNNs, LSTM/GRU networks, CNNs, DBNs, and DSN, and the frameworks to help get your neural network working quickly and well.
Also available in: Chinese   Japanese   Portuguese   Spanish  
Articles 08 Sep 2017
Build with Watson tips: Best practices for using custom classifiers in Watson Visual Recognition
Get best practice tips on using Watson services in this tutorial series.
Also available in: Chinese   Japanese   Portuguese   Spanish  
Articles 31 Aug 2017
Sample code: Translate natural language with the Watson Language Translator service
This code shows you how to use the Java API for the Watson language translator service. Given some text, a source language, and a target language, Watson translates that text and returns one or more translations to you.
Also available in: Chinese   Japanese  
Articles 18 Aug 2017
Sample code: Analyze text with the Watson Personality Insights service
This code shows you how to use the node.js API for the Watson Personality Insights service. Given some text, Watson analyzes the openness, conscientiousness, extraversion, agreeableness, emotional range, and needs of the speaker.
Also available in: Chinese   Japanese  
Articles 18 Aug 2017
Sample code: Identify the tone of written text with the Watson Tone Analyzer service
This code shows you how to use the node.js API for the Watson Tone Analyzer service. Given some text, Watson evaluates the tone, looking for qualities such as the speaker's levels of anger, disgust, joy, fear, and sadness.
Also available in: Chinese   Japanese  
Articles 18 Aug 2017
Sample code: Recognize and identify faces in an image with the Watson Visual Recognition service
This code shows you how to use the node.js API for the Watson Visual Recognition service. Given an image, Watson looks for faces in that image and attempts to recognize each of those faces.
Also available in: Chinese   Japanese  
Articles 17 Aug 2017
Recurrent neural networks deep dive
Explore the ideas behind recurrent neural networks and learn how to implement one from scratch for series data prediction.
Also available in: Chinese   Japanese  
Articles 17 Aug 2017
Teach Watson what results to surface
Train your private search collection by using Relevancy Training so that users can get the right answer to their question faster. See how Watson uses machine learning techniques to find specific signals in queries that can be applied against the corpus.
Also available in: Chinese   Japanese  
Articles 15 Aug 2017
Visualize and analyze data in proprietary and public datasets, Part 1: An overview of Watson for Real World Evidence
Get an introduction to IBM Watson for Real World Evidence, a cloud-based interactive Watson Health Life Sciences platform for decision makers, analysts, and data scientists to generate and test hypotheses.
Also available in: Chinese   Japanese  
Articles 10 Aug 2017
Visualize and analyze data in proprietary and public datasets, Part 3: Walk-through of a sample notebook
Get an introduction to IBM Watson for Real World Evidence, a cloud-based interactive Watson Health Life Sciences platform for decision makers, analysts, and data scientists to generate and test hypotheses.
Also available in: Chinese   Japanese  
Articles 10 Aug 2017
Visualize and analyze data in proprietary and public datasets, Part 2: A typical workflow
Get an introduction to IBM Watson for Real World Evidence, a cloud-based interactive Watson Health Life Sciences platform for decision makers, analysts, and data scientists to generate and test hypotheses.
Also available in: Chinese   Japanese  
Articles 10 Aug 2017
Extract insights from social media posts with Watson and Spark in Watson Studio
Combine Watson Developer Cloud services with analytics solutions that are optimized for big data to extract insights from social media posts.
Also available in: Chinese   Japanese  
Articles 09 Aug 2017
Add language translation to your apps with IBM Watson
Add language translation to your IBM Cloud apps. Use Node-RED and the Language Translation service to create an app that translates text that the user enters and performs sentiment analysis on that text.
Also available in: Chinese   Russian   Japanese   Spanish  
Articles 27 Jul 2017
A neural networks deep dive
In this tutorial, take a deeper look at neural networks. Read about their background and find out why neural networks are the dominant force in machine learning today.
Also available in: Chinese   Japanese  
Articles 24 Jul 2017
Developing cognitive IoT solutions for anomaly detection by using deep learning, Part 2: Generating data for anomaly detection
This article is the second in a five-part series, "Developing cognitive IoT solutions for anomaly detection by using deep learning." This article is a tutorial about using Node-RED to create a test data simulator.
Also available in: Chinese   Japanese   Portuguese   Spanish  
Articles 19 Jul 2017
Minecraft and IBM Cloud, Part 1: Running Minecraft servers within Docker
In this tutorial series, you'll learn how to use Docker, Eclipse, and IBM Cloud to develop, extend, and host your own Minehttp://www.ibm.com/developerworks/i/twitterdw-26796-minecraftseries.jpgcraft servers. Find out how to use Eclipse to build Minecraft plugins, test them locally using Docker, and use IBM Cloud to host your Docker containers on the Internet. You'll also harness the power of IBM Watson from within Minecraft for more educational and interactive game play. In Part 1, you'll set up your local Minecraft and Docker development environment, and see the power of Docker for building custom servers for Minecraft. You'll even get started playing with Minecraft on your own locally hosted server!
Also available in: Chinese   Japanese   Portuguese  
Articles 19 Jul 2017
Minecraft and IBM Cloud, Part 2: Building plugins for Minecraft with Docker and Eclipse
In this tutorial series, you'll learn how to use Docker, Eclipse, and IBM Cloud to develop, extend, and host your own Minecraft servers. Find out how to use Eclipse to build Minecraft plugins, test them locally using Docker, and use IBM Cloud to host your Docker containers on the Internet. You'll also harness the power of IBM Watson from within Minecraft for more educational and interactive game play. In Part 2, you'll set up your local development environment in Eclipse, then develop, build, and export your own server-side Minecraft plugin into a local Docker image.
Also available in: Chinese   Japanese   Portuguese  
Articles 19 Jul 2017
Developing cognitive IoT solutions for anomaly detection by using deep learning, Part 3: Using Deeplearning4j for anomaly detection
This article is the third in a five-part series, "Developing cognitive IoT solutions for anomaly detection by using deep learning." This article demonstrates a deep learning solution using Deeplearning4j and how it is used to analyze the large amount of data that IoT sensors gather.
Also available in: Chinese   Japanese   Portuguese   Spanish  
Articles 19 Jul 2017
Sample code: Translate natural language with the Watson Language Translator service
This code shows you how to use the node.js API for the Watson Language Translator service. Given some text, a source language, and a target language, Watson translates that text and returns one or more translations to you.
Also available in: Chinese   Japanese  
Articles 18 Jul 2017
Build and deploy a sample Liberty application to Bluemix
IBM introduced Watson services to the IBM Bluemix platform in early October 2014. This tutorial introduces the services and SDK currently available and describes how to deploy an application using the Watson Question and Answer service on Bluemix. The deployed application is a Java-based application.
Also available in: Chinese   Russian   Japanese  
Articles 18 Jul 2017
Sample code: Identify the context of natural language with the Watson Natural Language Classifier service
This code shows you how to use the Java API for the Watson natural language classification service. Given some text and a context, Watson analyzes the text and returns a list of categories relevant to that text.
Also available in: Chinese   Japanese  
Articles 18 Jul 2017
Sample code: Identify the context of natural language with the Watson Natural Language Classifier service
This code shows you how to use the node.js API for the Watson natural language classification service. Given some text and a context, Watson analyzes the text and returns a list of categories relevant to that text.
Also available in: Chinese   Japanese  
Articles 18 Jul 2017
Sample code: Analyze text with the Watson Personality Insights service
This code shows you how to use the Java API for the Watson Personality Insights service. Given some text, Watson analyzes the openness, conscientiousness, extraversion, agreeableness, emotional range, and needs of the speaker.
Also available in: Chinese  
Articles 18 Jul 2017
Sample code: Identify the tone of written text with the Watson Tone Analysis service
This code shows you how to use the Java API for the Watson tone analysis service. Given some text, Watson evaluates the tone, looking for qualities such as the speaker's levels of anger, disgust, joy, fear, and sadness.
Also available in: Chinese   Japanese  
Articles 18 Jul 2017
Sample code: Identify objects in an image with the Watson Visual Recognition service
This code shows you how to use the node.js API for the Watson Visual Recognition service. Given an image, Watson attempts to identify objects in that image.
Also available in: Chinese   Japanese  
Articles 18 Jul 2017
Find relevant information quickly with Passage Retrieval in Watson Discovery
Learn how Passage Retrieval, part of the IBM Watson Discovery Service, helps you find relevant information from within large amounts of unstructured data.
Also available in: Chinese   Japanese  
Articles 27 Jun 2017
Harness the power of IBM Watson Language Translator on IBM i
You can add powerful abilities to your IBM i applications by using IBM Bluemix Watson Services. The article illustrates how to create a Watson Language Translator service and obtain the credentials for accessing that service. It then provides several SQL statements that are used to access the translator service from IBM i. The article also describes how a Java program can be used to access the Watson Language Translator service.
Articles 21 Jun 2017
Speaking out loud
Natural language processing and other artificial intelligence-related technologies are all around us. Discover how the science began and where it might go in the future.
Also available in: Chinese   Japanese  
Articles 13 Jun 2017
Build a home assistant mobile application with Watson and IoT Platform services
The tutorial shows how a mobile application can use the Watson Assistant, Text to Speech, and Speech to Text services to understand user commands, which are then used to control devices through IBM IoT Platform services. It also shows how to integrate a Raspberry Pi as a home gateway that receives commands from and sends events to the mobile app. Finally, it shows how to store images by using Object Storage Service.
Also available in: Chinese   Japanese  
Articles 01 Jun 2017
A beginner's guide to artificial intelligence, machine learning, and cognitive computing
Get an overview of the history of artificial intelligence as well as the latest in neural network and deep learning approaches. Learn why, although AI and machine learning have had their ups and downs, new approaches like deep learning and cognitive computing have significantly raised the bar in these disciplines.
Also available in: Chinese   Japanese  
Articles 01 Jun 2017
Build a mobile app to analyze other apps with IBM Cloud, Watson Discovery, and Cloudant
Build a mobile app that provides an analysis of the reviews of the top 10 free apps in the App Store. The app then uses Cloudant to store the app details.
Also available in: Chinese   Japanese  
Articles 22 May 2017
5 things you need to know when creating a cognitive app
With the growth in applications that exploit the power of deep learning, artificial intelligence technologies are adding value to markets and applications across the board. This article explores five key concepts you should consider when developing an intelligent application.
Also available in: Chinese   Japanese  
Articles 17 May 2017
Developing cognitive IoT solutions for anomaly detection by using deep learning, Part 1: Introducing deep learning and long-short term memory networks
This article is the first in a five-part series, "Developing cognitive IoT solutions for anomaly detection by using deep learning." This article explains what deep learning is, what neural networks are, and how they can be used to analyze the large amount of data that IoT sensors gather.
Also available in: Chinese   Japanese  
Articles 16 May 2017
Creating a sentiment signal for publicly traded firms by using IBM Watson on Bluemix
This tutorial explains how our team used IBM Bluemix, the Watson Natural Language Understanding API, crawled web data, and Twitter data to create a web page to track the aggregated sentiment signal for several publicly traded firms. We also give two possible uses of this data in equity research.
Also available in: Chinese   Japanese  
Articles 09 May 2017
Build your chatbot with Watson Assistant
Learn how to integrate the Watson Assistant service with another Watson service, Natural Language Understanding, to expand the list of entities that can be extracted from users' speech.
Also available in: Chinese   Japanese  
Articles 02 May 2017
Explore the news and gather insights using Watson Discovery
Gather insights from big data by using the Watson Discovery service. Learn how to set up a Discovery instance on IBM Cloud and how you can run some common queries against the News collection.
Also available in: Chinese   Japanese  
Articles 10 Apr 2017
Introducing command line tools for Watson Visual Recognition
The Watson Visual Recognition service enables you to leverage cognitive computer vision to extract information from any image library. You can even go beyond standard object classification and use what are called ‘custom classifiers’ to train the Watson service to recognize specific items or conditions of your choosing. Read how the Watson Visual Recognition command line interface utility is used to interact with the service to train and test your custom classifiers.
Blog 21 Feb 2017
10 Steps to Train a Chatbot and its Machine Learning Models to Maximize Performance
The Watson Conversation Service offers a simple, scalable and science-driven solution for developers to build powerful chat bots to address the needs of various brands and companies. As developers leverage Watson Conversation to build cognitive solutions for various, one recurring question is: “How much time should I plan to train my solution” or “How do I know when my model is trained sufficiently well”? While the answer depends greatly on the problem being solved and the data powering the solution, in this blog we offer a common methodology for training the machine learning (ML) models powering your chat bot solution.
Blog 21 Feb 2017
Is Your Chatbot Ready for Prime-Time?
Despite the exponential growth in chatbots across various applications and messaging platforms, there are still several challenges to overcome when delivering a successful chatbot. One of the key challenges is the ability of the chatbot to understand the wide variety of inputs from the users. In this blog, we focus on computing and evaluating performance metrics for the trained machine learning system powering the chatbot.
Blog 21 Feb 2017
What is blockchain? A Primer on Distributed Ledger Technology
You’ve probably heard of Blockchain. It’s hard to navigate much of the web today without running across some kind of reference to it. After a while I thought, “Could I really explain Blockchain to someone if asked?” and if you’re in the same boat as I was, this post is for you.
Blog 21 Feb 2017
IBM Brings Machine Learning to Private Cloud
IBM has extracted the core machine learning technology from IBM Watson and will initially make it available where much of the world’s enterprise data resides: the z System mainframe, the operational core of global organizations where billions of daily transactions are processed.
Blog 16 Feb 2017
Create a chatbot, Part 1: Create a news chatbot to deliver content through Facebook Messenger
Create your own fully functional chatbot to deliver news and articles. This series shows you how to do this using two different messaging applications: Facebook Messenger and Slack. It then explains how to use IBM Watson services to enhance your chatbot. This tutorial explains how to build the chatbot to work with Facebook Messenger.
Also available in: Chinese  
Articles 06 Feb 2017
Create a chatbot, Part 2: Create a news chatbot to deliver content through Slack
Create your own fully functional chatbot to deliver news and articles. This series shows you how to do this using two different messaging applications: Facebook Messenger and Slack. It then explains how to use IBM Watson services to enhance your chatbot. This tutorial explains how to build the chatbot to work with Slack.
Also available in: Chinese  
Articles 06 Feb 2017
Create a chatbot, Part 3: Use cognitive (or artificial intelligence) services to enhance a chatbot
Create your own fully functional chatbot to deliver news and articles. This series shows you how to do this using two different messaging applications: Facebook Messenger and Slack. It then explains how to enhance your chatbot by using IBM Watson services. This third tutorial in the series explains the IBM Watson services that are used to enhance the chatbot.
Also available in: Chinese  
Articles 06 Feb 2017
Create a translation application by using Watson services, Eclipse, and IBM Cloud, Part 2: Add cognitive services to the app
In this series, learn how to create a translation application with a speech to text front end. The tutorials in the series cover how to set up your environment and then use Java programming to develop the cognitive services.
Also available in: Chinese  
Articles 31 Jan 2017
Build cognitive solutions for industries, Part 3: Design patterns for making cognitive data searchable and understandable
Cognitive computing is becoming increasingly important within the enterprise. In this tutorial, the third in a series, look at the design patterns for making cognitive data searchable and understandable.
Also available in: Chinese  
Articles 23 Jan 2017
Explore an architecture for connected assets in Maximo
Learn how to implement an asset management architecture by using inexpensive sensors, which are connected to Watson IoT Platform, which is then linked to Maximo Asset Health Insights.
Also available in: Chinese  
Articles 18 Jan 2017
Create a translation application by using Watson services, Eclipse, and IBM Cloud, Part 1: Set up the environment
In this series, learn how to create a translation application with a speech to text front end. The tutorials in the series cover setting up your environment and then using Java programming to develop the cognitive services.
Also available in: Chinese   Portuguese  
Articles 05 Dec 2016
Build cognitive solutions for industries, Part 2: Use cases for industry cognitive solutions
Cognitive computing is becoming increasingly important within the enterprise. In this tutorial, the second in a series, explore multiple successful cognitive use cases to help you understand what can be accomplished by building a cognitive platform.
Also available in: Chinese   Japanese  
Articles 12 Oct 2016
Build cognitive solutions for industries, Part 1: Cognitive computing in the Telecommunication and Media & Entertainment industries
Cognitive computing is becoming increasingly important within the enterprise. In this tutorial, the first in a series, learn how you can design and implement cognitive solutions in your own environment.
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Articles 28 Sep 2016
Ask Watson what Twitter is telling you, Part 4: Extract image text and analyze sentiments
Quickly build an app to get data from Twitter and then use the data for cognitive insights by using IBM Watson services such as Tone Analyzer, Visual Recognition, and Alchemy. In just a few minutes, you can create a running Python app on Bluemix that analyzes pictures that are included in tweets.
Also available in: Chinese   Japanese  
Articles 22 Aug 2016
Build an SMS monitoring app with Bluemix and Twilio's IBM Watson Add-ons
IBM Watson Message Insights and Sentiment Analysis are now available as Add-ons in the Twilio marketplace. In this tutorial, learn how to harness the power of these services by enriching SMS messages sent to a Twilio service with IBM Watson, and route these enriched messages to a Bluemix web application. In six easy steps, you can deploy a Bluemix application, configure your Twilio account, and visualize the value of IBM Watson for your text message augmentation needs!
Also available in: Japanese  
Articles 15 Aug 2016
The conversational chatbox design challenge
Learn the key issues that you face with conversational design in chatbots. Find out how to make your chatbot successful by looking at messaging platforms, types of interactions, and user inputs and responses.
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Articles 15 Aug 2016
A developer's guide to chatbots
One of the current trends in technology is the chatbot. This tutorial summarizes the major messaging platforms, bot frameworks, and artificial intelligence (AI) services you use to develop your chatbot applications.
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Articles 10 Aug 2016
Improve the customer experience with cognitive computing and IBM Watson
Discover how a hypothetical bank uses IBM Watson services to enhance their loyalty program. By focusing on a few key services, they can gain insights into their customers' personalities and predict their behavior and preferences, allowing them to personalize rewards. Using Tone Analyzer in a live chat also helps customer representatives more accurately read the customers' tone and so the customer reps can adjust their own tone while typing.
Also available in: Japanese  
Articles 01 Aug 2016
Machine Learning, Deep Learning 101
This article describes the growing relevance of Machine Learning used in various kinds of analytics along with an overview of Deep Learning. It provides an end-to-end process for using Machine Learning and Deep Learning and the options for getting started on IBM® Power Systems™.
Also available in: Chinese   Japanese  
Articles 20 Jul 2016
Ask Watson what Twitter is telling you, Part 3: Analyze tweet pictures for categorization and recognition
Quickly build an app to get data from Twitter and then use the data for cognitive insights by using IBM Watson services such as Tone Analyzer, Visual Recognition, and Alchemy. In just a few minutes, you can create a running Python app on IBM Cloud that analyzes pictures that are included in tweets.
Also available in: Chinese   Japanese  
Articles 19 Jul 2016
Ask Watson what Twitter is telling you, Part 2: Analyze the tweet text for emotions
Quickly build an app to get data from Twitter and then use the data for cognitive insights by using IBM Watson services such as Tone Analyzer, Visual Recognition, and Alchemy. You can drill down on the sentiments by analyzing the text right down to the sentence level. You then share your findings through a bar graph of emotions.
Also available in: Chinese   Japanese  
Articles 28 Jun 2016
Integrate Business Rules with Watson services on IBM Bluemix, Part 2: Build a job matching app with Play Framework that integrates Personality Insights and Business Rules services
This series guides you through creating an application that uses the Business Rules service on IBM Bluemix and automates decisions based on the results of the Personality Insights service. In Part 2, you develop an example personality-driven job matching application with Play Framework, and you deploy it on Bluemix with a custom Java build pack. The example application demonstrates how you can run, integrate, and deploy the Personality Insights, Business Rules, and ClearDB MySQL Database services on Bluemix.
Articles 28 Jun 2016
Integrate Business Rules with Watson services on IBM Bluemix, Part 1: Build a Business Rules app that uses Personality Insights to match job applicants
This series guides you through creating an application that uses the Business Rules service on IBM Bluemix and automates decisions based on the results of the Personality Insights service. Part 1 describes how you can use the Business Rules service to construct and deploy business rules on Bluemix, based on the Personality Insights data. You learn how to define a Business Rules data model from the Personality Insights data model. Finally, you learn how to deploy and test the Personality Insights-driven Business Rules project on Bluemix.
Articles 23 Jun 2016
Ask Watson what Twitter is telling you, Part 1: Getting your Twitter credentials
Quickly build an app to get data from Twitter and then use the data for cognitive insights by using IBM Watson services such as Tone Analyzer, Visual Recognition, and Alchemy.
Also available in: Chinese   Japanese  
Articles 20 Jun 2016
Create a browser-based PDF storage and search application with Bluemix services, Part 1: Use the Document Conversion and Keyword Extraction services to convert and index files
In Part 1 of this two-part series, learn how to create a powerful, browser-based, document storage and search application that makes it faster and easier to search for relevant content in your documents. The application uses the Slim PHP micro-framework, together with Document Conversion and Keyword Extraction services from IBM Watson. IBM Bluemix provides object storage services and hosting infrastructure.
Also available in: Japanese   Spanish  
Articles 13 Jun 2016
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