AI Blueprints

Description

AI Blueprints gives you a working framework and the techniques to build your own successful AI business applications. You’ll learn across six business scenarios how AI can solve critical challenges with state-of-the-art AI software libraries and a well thought out workflow. Along the way you’ll discover the practical techniques to build AI business applications from first design to full coding and deployment. The AI blueprints in this book solve key business scenarios. The first blueprint uses AI to find solutions for building plans for cloud computing that are on-time and under budget. The second blueprint involves an AI system that continuously monitors social media to gauge public feeling about a topic of interest - such as self-driving cars. You’ll learn how to approach AI business problems and apply blueprints that can ensure success. The next AI scenario shows you how to approach the problem of creating a recommendation engine and monitoring how those recommendations perform. The fourth blueprint shows you how to use deep learning to find your business logo in social media photos and assess how people interact with your products. Learn the practical techniques involved and how to apply these blueprints intelligently. The fifth blueprint is about how to best design a ‘trending now’ section on your website, much like the one we know from Twitter. The sixth blueprint shows how to create helpful chatbots so that an AI system can understand customers’ questions and answer them with relevant responses. This book continuously demonstrates a working framework and strategy for building AI business applications. Along the way, you’ll also learn how to prepare for future advances in AI. You’ll gain a workflow and a toolbox of patterns and techniques so that you can create your own smart code. AI Blueprints Why subscribe? Packt.com Foreword Contributors About the author About the reviewer Packt is searching for authors like you Preface Who this book is for What this book covers What you need for this book Download the example code files Download the color images Conventions used Get in touch Reviews 1. The AI Workflow AI isn't everything The AI workflow Characterize the problem Checklist Develop a method Checklist Design a deployment strategy Checklist Design and implement a continuous evaluation Checklist Overview of the chapters Summary 2. A Blueprint for Planning Cloud Infrastructure The problem, goal, and business case Method – constraint solvers OptaPlanner Deployment strategy Continuous evaluation Summary 3. A Blueprint for Making Sense of Feedback The problem, goal, and business case Method – sentiment analysis Deployment strategy CoreNLP processing pipeline Twitter API The GATE platform Reddit API News API Dashboard with plotly.js and Dash Continuous evaluation Retraining CoreNLP sentiment models Summary 4. A Blueprint for Recommending Products and Services Usage scenario – implicit feedback Content-based recommendations Collaborative filtering recommendations BM25 weighting Matrix factorization Deployment strategy Continuous evaluation Calculating precision and recall for BM25 weighting Online evaluation of our recommendation system Summary 5. A Blueprint for Detecting Your Logo in Social Media The rise of machine learning Goal and business case Neural networks and deep learning Deep learning Convolutions Network architecture Activation functions TensorFlow and Keras YOLO and Darknet Continuous evaluation Summary 6. A Blueprint for Discovering Trends and Recognizing Anomalies Overview of techniques Discovering linear trends Discovering dynamic linear trends with a sliding window Discovering seasonal trends ARIMA Dynamic linear models Recognizing anomalies Z-scores with static models Z-scores with sliding windows RPCA Clustering Deployment strategy Summary 7. A Blueprint for Understanding Queries and Generating Responses The problem, goal, and business case Our approach The Pokémon domain The course advising domain Method – NLP + logic programming + NLG NLP with Rasa Logic programming with Prolog and tuProlog Prolog unification and resolution Using Prolog from Java with tuProlog Pokémon in Prolog Natural language generation with SimpleNLG A second example – college course advising Continuous evaluation Summary 8. Preparing for Your Futureand Surviving the Hype Cycle Always one step ahead The state of things Natural language processing Computer vision Expert systems and business rules Planning and scheduling Robotics Understanding the hype cycle of AI The next big thing Summary Other Books You May Enjoy Leave a review - let other readers know what you think Index