📕 subnode [[@KGBicheno/main ai page]]
in 📚 node [[main-ai-page]]
Go back to [[Master Contents Page]]
Introduction to AI
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[[Week 1 - Introduction]]
- [[Introducing AI]]
- [[What is AI]]
- [[Tanmay's Journey and take on AI]]
- [[AI is not magic - Demystify and Apply]]
- [[Women leaders in AI]]
- [[AI and the time to be creative]]
- [[AI in the media - Key questions to consider]]
- [[AI needs barriers to be successful]]
- [[AI requires buy-in from leadership]]
- [[AI's Ratchet effect]]
- [[AI-specific pain points]]
- [[Comparison of not having an AI plan in 2020]]
- [[Diversity lowers the risk of AI]]
- [[Examples and impact of AI (LIST)]]
- [[Expert Insights - AI fast forwards video for sports highlights]]
- [[Find an AI mentor]]
- [[Get To AI At Scale]]
- [[Prioritisation]]
- [[Prove the value of AI]]
- [[PWC study - AI's impact on GDP by 2030]]
- [[The 3 Foundations - (AI) is only as good as your (IA)]]
- [[The AI Job Replacement Axiom]]
- [[The AI Ladder]]
- [[The next 10,000 business cases - Kevin Kelly]]
- [[Time-Proportion Value Increase of the Journalist]]
- [[Two Key Elements Of AI - Componentry and Process]]
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[[Week 2 - Introduction]]
- [[Adaptive resonance theory]]
- [[Four stages of human cognition]]
- [[How to get started with Cognitive Technology]]
- [[Adoption starts with education]]
- [[IBM's cognitive advantage global market report]]
- [[The Three patterns of AI technology usage]]
- [[Adoption starts with education]]
- [[Best practice - AI lessons from early adopters]]
- [[Build, deploy or collaborate]]
- [[Checklist for AI Adoption]]
- [[Four main categories of AI implementation]]
- [[Four stages of human cognition]]
- [[Functional Patterns]]
- [[Goal-based Patterns]]
- [[k-means clustering]]
- [[Technology Patterns]]
- [[Project Debater - Understanding each other through AI]]
- [[Quote the numbers - benefits of AI adoption]]
- [[Woodside - AI causes growth in jobs]]
- [[Machine Learning]]
- [[Supervised Learning]]
- [[Regression - supervised learning]]
- [[Classification - supervised learning]]
- [[Reinforcement - supervised learning]]
- [[Unsupervised Learning]]
- [[Training your model]]
- [[Three ways to evaluate models]]
- [[Deep Learning]]
- [[Neural Networks]]
- [[Back-propagation]]
- [[Perceptrons]]
- [[Bias]]
- [[Artificial Intelligence/Introduction to AI/Week 2 - Introduction/Activation function]]
- [[CNNS - Convolutional neural networks]]
- [[RNNS - Recurrent neural networks]]
- [[Artificial Intelligence/Introduction to AI/Week 2 - Introduction/Natural Language Processing]]
- [[Modern Approaches in NLP]]
- [[Recurrent Neural Networks in NLP]]
- [[Reinforcement Learning in NLP]]
- [[Deep Learning in NLP]]
- [[Long short-term memory - LSTM]]
- [[Gated Recurrent Unit]]
- [[Artificial Intelligence/Introduction to AI/Week 2 - Introduction/Activation function]]
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[[Week 3 - Introduction]]
- [[The threat to journalists' jobs]]
- [[Journalists' jobs will have to change]]
- [[AI and regaining market share]]
- [[Can Journalists and AI Cooperate - or is it war]]
- [[AI and differentiation free vs paywalled content]]
- [[Collating meta-content with AI]]
- [[Creatives have already been replaced in places]]
- [[Using AI to fact-check and verify information]]
- [[Popularity of AI journalistic tools]]
- [[Autogeneration of news content]]
- [[Sports, fans, and data-chewing bots]]
- [[Bots for news content]]
- [[Bots for comments moderation]]
- [[AI and regaining market share]]
- [[AI is 'polysemous' - accumulates meanings]]
- [[AI is here, most unaware]]
- [[AI will purify the use of journalistic skills]]
- [[Autogeneration of news content]]
- [[Beware when using traditional messaging theory around AI]]
- [[Collating meta-content with AI]]
- [[Creativity buffering jobs from AI takeover]]
- [[Current uses of Natural Language Generated content]]
- [[Editors resist fully automated news process]]
- [[Natural Language Generation]]
- [[Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Natural Language Processing]]
- [[News Media industry changes caused by AI]]
- [[Opinions on AI replacing jobs]]
- [[Optimising the editorial work process with AI]]
- [[Origin stories of AI in News Media and Journalism]]
- [[Popularity of AI journalistic tools]]
- [[Recurring origin stories of AI]]
- [[Saad and Issa's use of AI in journalism]]
- [[Sports, fans, and data-chewing bots]]
- [[Tech has changed Journo hiring priorities]]
- [[The threat to journalists' jobs]]
- [[Traditional journalism driving AI, not AI driving journalism]]
- [[Translating worldwide news with AI]]
- [[Unsupervised Neural Networks for detecting Fake News]]
- [[Week 4 - Introduction]]
Creating Chatbots with Watson
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[[Building AI-powered Chatbots with Watson]]
- [[Introduction to Chatbots]]
- [[What are Chatbots]]
- [[The First Chatbot - Eliza]]
- [[Seven most important conversational computing providers]]
- [[Nine Criteria for evaluating Chatbot vendors]]
- [[IBM Watson Assistant]]
- [[Amazon Alexa]]
- [[Google Dialogflow]]
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[[How to build a Chatbot with Watson Assistant]]
- [[Intents]]
- [[Entities]]
- [[Dialogues]]
- [[Context Variables and Slots]]
- [[IBM Notes on Chatbot writing]]
- [[Preparing a Chatbot for deployment]]
- [[API details for the Flower Shop Assistant]]
- [[Dummy WordPress site Credentials]]
- [[Deploying a Chatbot to Wordpress]]
Watson Overview
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[[Module 1 - Watson AI Overview]]
- [[The business importance of recording interactions]]
- [[Transfer Learning - IBM]]
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[[Watson AI is changing how business is done]]
- [[Expertice on call]]
- [[Expert service - 60 per cent faster]]
- [[AR-powered technician support]]
- [[Customer response in seconds - not minutes]]
- [[Market data in plain language]]
- [[Confidence in the details]]
- [[Answering tomorrow's legal questions]]
- [[Predicting and preventing breakdowns]]
- [[Preserving institutional wisdom]]
- [[Claims assessed 25 per cent faster]]
- [[Maintenance done 90 per cent faster]]
- [[Expected AI spend next year (2021)]]
- [[Four key principles of Watson]]
- [[How AI amplifies an employee's role]]
- [[How to get IBM on board]]
- [[Watson Explorer]]
- [[Watson with Audits and Compliance]]
- [[Module 2 - Available Watson Services]]
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[[Module 3 - Advanced Watson Services]]
- [[Watson at LivePerson Contact Centres]]
- [[Watson Compare and Comply]]
- [[Watson Knowledge Catalogue]]
- [[Watson Machine Learning]]
- [[Watson OpenScale]]
- [[Watson Personality Insights]]
- [[Watson Studio]]
- [[Watson Tone Analyser]]
- [[Big 5 personality model]]
- [[Computer Vision, its applications, and IBM Watson]]
- [[Open Source Replacements - TODO]]
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[[Module 4 - Watson Use Cases and Resources List]]
- [[Watson At Work]]
- [[Toby - Watson's use cases]]
- [[Bradesco]]
- [[Watson for Oncology, Clinical Trial Matching, and Genomics]]
- [[Watson in use at Coca-Cola Company]]
- [[Watson at ADNOC]]
- [[Watson in use at KONE]]
- [[Watson at LivePerson]]
- [[Watson at Hilton]]
- [[402_solutionbrief_200401_openscale_copyupdate_14020014USEN_.pdf]]
- [[Data_Science_Pipeline_Readiness.pdf]]
- [[ESG-Tech-Validation-IBM-Watson-Studio-Feb-2019.pdf]]
- [[How_to_get_IBM_on_board.mp4]]
- [[Watson_services.mp4]]
- [[Watson_Studio.mp4]]
- [[Watson_Compare_And_Comply.mp4]]
- [[Watson_call_centre_solution.mp4]]
- [[IBM_Watson_Professional_Solutions_Certification.pdf]]
Python for Data Science and AI
- [[Python Week 1 Main Page]]
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[[Python Week 2 Main Page]]
- [[Python Lists and Tuples]]
- [[Week2 Tuples Lab]]
- [[Week2 Lists Lab]]
- [[Python Dictionaries]]
- [[Week2 Dictionaries Lab]]
- [[Python Sets]]
- [[Week2 Sets Lab]]
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[[Python Week 3 Main Page]]
- [[Python Conditions and Branching]]
- [[Week3 Conditions and Branching Lab]]
- [[Python Loops - For Loops]]
- [[Python Loops - While Loops]]
- [[Week3 Python For and While Loops Lab]]
- [[Python Functions]]
- [[Python Function Scope - Global vs Local]]
- [[Week3 Functions and Scope Lab]]
- [[Python Classes]]
- [[Week3 Classes and Objects Lab]]
- [[Python Week 4 Main Page]]
- [[Python Week 5 Main Page]]
Deploying IBM AI Services
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[[AI Service Deployment Main Page]]
- [[Creating a Discovery Collection]]
- [[Data vs Insight]]
- [[Advanced Watson Discovery]]
- [[Creating a Watson Chatbot with Discovery]]
- [[Integrating Discovery and Assistant]]
- [[Adding Watson Speech Services]]
- [[Voice Options for your Chatbot]]
- [[Deployment Options for Watson Speech Assistant]]
- [[Deploying your Watson Assistant to Facebook Messenger]]
- [[Deploying your Watson Assistant to Slack]]
Resources
- [[Exxact_Quote_100274-1.pdf]]
- [[Pasted image.png]]
- [[Professional Machine Learning Workstation - Exxact Quote]]
- [[Recommended algorithms by usage]]
- [[HistoryOfAI.jpeg]]
- [[Creating Chatbots with Watson.pdf]]
- [[Creating_Intents.pdf]]
- [[Define_Domain_Specific_Intents.pdf]]
- [[Create_Entities.pdf]]
- [[Import_and_Export_Entities.pdf]]
- [[Implement_the_Dialog.pdf]]
- [[Add_a_preview_and_retrieve_your_credentials.pdf]]
- [[Deploy_your_Chatbot.pdf]]
- [[Explore_Context_Variables.pdf]]
- [[Master_Slots.pdf]]
- [[Enable_Digressions.pdf]]
- [[Get_to_know_the_Analytics_tab.pdf]]
- [[Pasted image 20201103162748.png]]
- [[IBM_Python_for_Data_Science_Professional.pdf]]
See also the [[The Golem Project Overview]] for the ultimate implementation of this and the [[Master of Philosophy]].
For a professionally designed workstation built for machine learning, check out the [[Professional Machine Learning Workstation - Exxact Quote]]
For a discontinued project that may still be of educational value, see the [[Main Library - Chatterbot]] and [[Why I didn't use Chatterbot]].
Currently my most popular bot is Floria from The AFIRM project, which you can read about at the [[AFIRM Overall Project Page]]
Most, it not all code is written in Python, and will link through the [[Python - Main Page]]
📖 stoas
- public document at doc.anagora.org/main-ai-page
- video call at meet.jit.si/main-ai-page