by Swami Chandrasekaran | Released November 2018 | ISBN: 9781788620789

Making your applications smart by combining Cognitive and AI capabilitiesAbout This VideoA comprehensive and friendly guide to getting started with IBM Watson.Covers the latest version of IBM Watson with fully up-to-date techniques and code examples.Shows how to add the different features of Watson in your applicationIn DetailIBM Watson has evolved from being a game show winning question & answering computer system to a set of enterprise-grade artificial intelligence (AI) application program interfaces (API) available on IBM Cloud. These Watson API's can ingest, understand & analyze all forms of data, allow for natural forms of interactions with people, learn, reason - all at a scale that allows for business processes and applications to be reimagined. This course will give you a hands-on introduction to getting a detailed understanding of the Watson AI API's, how to train them and eventually build applications using them. You will go through the fundamentals behind each of the API's, lots of code examples on how to use them on different types of unstructured data, spot the scenarios where you can apply them as well as real-life use case examples. You will learn about how to build conversational apps a.k.a., chat-bots, analyze text at a deeper level, transcribe audio, training a machine to classify & detect objects in pictures, extract entities, emotions, sentiment and relationships from news articles etc. You will also learn the different types of data basics of AI including machine & deep learning, approach to building AI systems. You will learn about the basics of getting started with IBM Cloud, Watson and setting up an environment to build AI infused apps.By the end of the course, you will have a complete understanding of the various Watson API's and will have developed the skills to effectively use them in applications and business processes you may be working on.All the code and supporting files for this course are available at: https://github.com/PacktPublishing/Learning-to-Build-Apps-Using-Watson-AI Show and hide more

1. Chapter 1 : Introducing the IBM Watson Platform
   • The Course Overview 00:10:47
   • Fundamentals 00:10:02
   • Fundamentals – Part 2 00:07:24
   • Introducing IBM Watson 00:08:58
   • The IBM Watson Platform 00:14:53
   • Adapting Watson 00:06:49
   • Examples 00:03:47
2. Chapter 2 : Getting Started with coding for IBM Watson
   • Watson API’s 00:09:07
   • IBM Cloud 00:04:06
   • Development Environment 00:10:40
   • Hello Watson 00:08:45
   • Hello Watson (Continued) 00:04:10
   • IBM Node-RED 00:08:03
   • IBM Node-RED (Continued) 00:07:54
   • Python and Node.js SDK 00:06:56
   • Python and Node.js SDK (Continued) 00:08:25
3. Chapter 3 : Build Conversational Systems Using the Watson Conversation Service
   • Watson Assistant in Depth 00:15:41
   • Watson Assistant in Depth (continued) 00:14:05
   • Define Intents and Entities Workspace 00:20:20
   • Define Intents 00:19:31
   • Define Entities 00:20:50
   • Build Dialog Overview 00:11:23
   • Build Dialog Conditions and Responses 00:10:34
   • Build Dialog Context, Slots and Folders 00:26:20
   • Build Dialog Advanced Responses and APIs 00:14:45
   • Evaluate and Deploy the Model 00:18:11
   • Build: IT Support Assistant 00:24:07
   • Improving Models Continuously 00:08:52
   • Applying the Capability in Various Use Cases 00:06:38
4. Chapter 4 : Rich Text Analytics Using Watson Natural Language Understanding for Your Application
   • Watson NLU in Depth 00:15:05
   • Watson NLU in Depth – Part 2 00:08:01
   • Understand Entities and Relations 00:14:54
   • Concepts, Categories, and Keywords 00:08:02
   • Sentiment and Document Emotion 00:06:26
   • Build: Analyzing Customer Complaints 00:07:41
   • Build: Analyzing Customer Complaints – Part 2 00:16:46
   • Applying NLU in Various Use Cases 00:09:04
5. Chapter 5 : Adding Speech Recognition Capabilities to Your Apps Using Watson Speech to Text
   • Watson Speech to Text in Depth 00:23:58
   • Watson Speech to Text in Depth (Continued) 00:18:34
   • Key Concepts 00:09:14
   • Key Concepts (Continued) 00:31:03
   • Testing Watson Speech To Text Model 00:14:40
   • Improving STT Model Using Custom Words 00:18:16
   • Improving STT Model Using Custom Words(continued) 00:16:09
   • Build Your Own Custom Acoustic Model 00:16:23
   • Build: Company Earnings Call Transcript Application 00:13:26
   • Applying the Capability in Various Use Cases 00:09:16
6. Chapter 6 : Train Image Recognition Models Using Watson Visual Recognition
   • Watson Visual Recognition in Depth 00:19:01
   • Watson Visual Recognition in Depth (Continued) 00:14:25
   • Classifying Images 00:10:21
   • Classifying Images (Continued) 00:07:40
   • Detecting Food and Faces 00:05:22
   • Extracting Text from Images 00:03:12
   • Introduction to Watson Studio 00:11:41
   • Overall Approach to Training 00:12:14
   • Training the Classifier 00:08:44
   • Invoke Model, Best Practices and Applicable Cases 00:13:34
   • Apply the Capability in Various Use Cases and Convert to Core ML 00:08:10
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