Low-Code AI

Low-Code AI PDF Author: Gwendolyn Stripling
Publisher: "O'Reilly Media, Inc."
ISBN: 1098146786
Category : Computers
Languages : en
Pages : 347

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Book Description
Take a data-first and use-case–driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on guide presents three problem-focused ways to learn no-code ML using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. In each case, you'll learn key ML concepts by using real-world datasets with realistic problems. Business and data analysts get a project-based introduction to ML/AI using a detailed, data-driven approach: loading and analyzing data; feeding data into an ML model; building, training, and testing; and deploying the model into production. Authors Michael Abel and Gwendolyn Stripling show you how to build machine learning models for retail, healthcare, financial services, energy, and telecommunications. You'll learn how to: Distinguish between structured and unstructured data and the challenges they present Visualize and analyze data Preprocess data for input into a machine learning model Differentiate between the regression and classification supervised learning models Compare different ML model types and architectures, from no code to low code to custom training Design, implement, and tune ML models Export data to a GitHub repository for data management and governance

Low-Code AI

Low-Code AI PDF Author: Gwendolyn Stripling
Publisher: "O'Reilly Media, Inc."
ISBN: 1098146786
Category : Computers
Languages : en
Pages : 347

Get Book Here

Book Description
Take a data-first and use-case–driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on guide presents three problem-focused ways to learn no-code ML using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. In each case, you'll learn key ML concepts by using real-world datasets with realistic problems. Business and data analysts get a project-based introduction to ML/AI using a detailed, data-driven approach: loading and analyzing data; feeding data into an ML model; building, training, and testing; and deploying the model into production. Authors Michael Abel and Gwendolyn Stripling show you how to build machine learning models for retail, healthcare, financial services, energy, and telecommunications. You'll learn how to: Distinguish between structured and unstructured data and the challenges they present Visualize and analyze data Preprocess data for input into a machine learning model Differentiate between the regression and classification supervised learning models Compare different ML model types and architectures, from no code to low code to custom training Design, implement, and tune ML models Export data to a GitHub repository for data management and governance

Low-Code AI

Low-Code AI PDF Author: Gwendolyn Stripling
Publisher: "O'Reilly Media, Inc."
ISBN: 1098146794
Category : Computers
Languages : en
Pages : 328

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Book Description
Take a data-first and use-case–driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on guide presents three problem-focused ways to learn no-code ML using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. In each case, you'll learn key ML concepts by using real-world datasets with realistic problems. Business and data analysts get a project-based introduction to ML/AI using a detailed, data-driven approach: loading and analyzing data; feeding data into an ML model; building, training, and testing; and deploying the model into production. Authors Michael Abel and Gwendolyn Stripling show you how to build machine learning models for retail, healthcare, financial services, energy, and telecommunications. You'll learn how to: Distinguish between structured and unstructured data and the challenges they present Visualize and analyze data Preprocess data for input into a machine learning model Differentiate between the regression and classification supervised learning models Compare different ML model types and architectures, from no code to low code to custom training Design, implement, and tune ML models Export data to a GitHub repository for data management and governance

Artificial Intelligence Basics

Artificial Intelligence Basics PDF Author: Tom Taulli
Publisher: Apress
ISBN: 1484250281
Category : Computers
Languages : en
Pages : 195

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Book Description
Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and many more. In our modern era, an understanding of AI and its possibilities for your organization is essential for growth and success. Artificial Intelligence Basics has arrived to equip you with a fundamental, timely grasp of AI and its impact. Author Tom Taulli provides an engaging, non-technical introduction to important concepts such as machine learning, deep learning, natural language processing (NLP), robotics, and more. In addition to guiding you through real-world case studies and practical implementation steps, Taulli uses his expertise to expand on the bigger questions that surround AI. These include societal trends, ethics, and future impact AI will have on world governments, company structures, and daily life. Google, Amazon, Facebook, and similar tech giants are far from the only organizations on which artificial intelligence has had—and will continue to have—an incredibly significant result. AI is the present and the future of your business as well as your home life. Strengthening your prowess on the subject will prove invaluable to your preparation for the future of tech, and Artificial Intelligence Basics is the indispensable guide that you’ve been seeking. What You Will Learn Study the core principles for AI approaches such as machine learning, deep learning, and NLP (Natural Language Processing)Discover the best practices to successfully implement AI by examining case studies including Uber, Facebook, Waymo, UiPath, and Stitch FixUnderstand how AI capabilities for robots can improve businessDeploy chatbots and Robotic Processing Automation (RPA) to save costs and improve customer serviceAvoid costly gotchasRecognize ethical concerns and other risk factors of using artificial intelligenceExamine the secular trends and how they may impact your business Who This Book Is For Readers without a technical background, such as managers, looking to understand AI to evaluate solutions.

Deep Learning for Coders with fastai and PyTorch

Deep Learning for Coders with fastai and PyTorch PDF Author: Jeremy Howard
Publisher: O'Reilly Media
ISBN: 1492045497
Category : Computers
Languages : en
Pages : 624

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Book Description
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Artificial Intelligence for Developers in easy steps

Artificial Intelligence for Developers in easy steps PDF Author: Richard Urwin
Publisher: In Easy Steps Limited
ISBN: 1787910253
Category : Computers
Languages : en
Pages : 302

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Book Description
Artificial Intelligence for Developers in easy steps is for coders who want to enhance their skillset quickly and easily. Artificial Intelligence (AI) is here to stay, and this guide reveals how AI works and illustrates how to build AI applications. It even covers no-code AI tools. This primer comes with free downloadable source code to get you started straightaway. Topics covered include: · Creating a chatbot. · Building an expert system. · Understanding the flatworld, fuzzy logic, and subsumption architecture. · Genetic algorithms, neural networks, generative AI, and low code. Aimed at aspiring developers and students who are familiar with Python and now want to master AI concepts and build intelligent AI solutions. AI programming is mainstream now. Update your coding skills and stay on top! Table of Contents 1. Introducing artificial intelligence 2. Creating a chatbot 3. Expert systems 4. The flatworld 5. Fuzzy logic 6. Subsumption architecture 7. Genetic algorithms 8. Neural networks 9. Pretrained neural networks 10. Generative artificial intelligence 11. Low code

AI-Assisted Programming

AI-Assisted Programming PDF Author: Tom Taulli
Publisher: "O'Reilly Media, Inc."
ISBN: 1098164520
Category : Computers
Languages : en
Pages : 231

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Book Description
Get practical advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, design, coding, debugging, testing, and documentation. With this book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs (ChatGPT, Gemini, and Claude) to code-specific systems (GitHub Copilot, Tabnine, Cursor, and Amazon CodeWhisperer). You'll also learn about more specialized generative AI tools for tasks such as text-to-image creation. Author Tom Taulli provides a methodology for modular programming that aligns effectively with the way prompts create AI-generated code. This guide also describes the best ways of using general purpose LLMs to learn a programming language, explain code, or convert code from one language to another. This book examines: The core capabilities of AI-based development tools Pros, cons, and use cases of popular systems such as GitHub Copilot and Amazon CodeWhisperer Ways to use ChatGPT, Gemini, Claude, and other generic LLMs for coding Using AI development tools for the software development lifecycle, including requirements, planning, coding, debugging, and testing Prompt engineering for development Using AI-assisted programming for tedious tasks like creating regular expressions, starter code, object-oriented programming classes, and GitHub Actions How to use AI-based low-code and no-code tools, such as to create professional UIs

AI-Assisted Programming

AI-Assisted Programming PDF Author: Tom Taulli
Publisher: "O'Reilly Media, Inc."
ISBN: 1098164571
Category : Computers
Languages : en
Pages : 225

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Book Description
Get practical advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, design, coding, debugging, testing, and documentation. With this book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs (ChatGPT, Gemini, and Claude) to code-specific systems (GitHub Copilot, Tabnine, Cursor, and Amazon CodeWhisperer). You'll also learn about more specialized generative AI tools for tasks such as text-to-image creation. Author Tom Taulli provides a methodology for modular programming that aligns effectively with the way prompts create AI-generated code. This guide also describes the best ways of using general purpose LLMs to learn a programming language, explain code, or convert code from one language to another. This book examines: The core capabilities of AI-based development tools Pros, cons, and use cases of popular systems such as GitHub Copilot and Amazon CodeWhisperer Ways to use ChatGPT, Gemini, Claude, and other generic LLMs for coding Using AI development tools for the software development lifecycle, including requirements, planning, coding, debugging, and testing Prompt engineering for development Using AI-assisted programming for tedious tasks like creating regular expressions, starter code, object-oriented programming classes, and GitHub Actions How to use AI-based low-code and no-code tools, such as to create professional UIs

The AI Revolution in Networking, Cybersecurity, and Emerging Technologies

The AI Revolution in Networking, Cybersecurity, and Emerging Technologies PDF Author: Omar Santos
Publisher: Addison-Wesley Professional
ISBN: 0138293635
Category : Computers
Languages : en
Pages : 336

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Book Description
The AI Revolution is Here. Discover its Dynamic Applications in Networking, Cybersecurity, and More. AI is having a profound impact on nearly every sector of the workforce. Huge professional and financial opportunities await in the key domains of computer networking, cybersecurity, IoT, and cloud computing. The AI Revolution in Networking, Cybersecurity, and Emerging Technologies will give you the edge you need to harness AI for your benefit. Learn how AI can efficiently identify shadow data, fortify security measures, generate predictive analytics in real time, and so much more. In this comprehensive guide, Cisco professionals Omar Santos, Samer Salam, and Hazim Dahir engage you in both AI application and theory through practical case studies and predictions of future trends, which makes this book not just a valuable guide for today, but an indispensable resource for tomorrow. You'll discover how AI is building robust bridges in collaboration tools and turning IoT into a super-intelligent network of devices so you can quickly identify and resolve network security threats while enhancing network performance. This book will show you how AI can help you modernize and fortify your operations and make yourself a key asset to your company. Are you ready to join The AI Revolution in Networking, Cybersecurity, and Emerging Technologies? Gain industry-specific knowledge from experienced professionals Discover new capabilities like self-healing networks and predictive analytics Learn how AI can save time by detecting and correcting issues in real time Master techniques for security monitoring and alerting Understand potential security and privacy pitfalls of using AI, and how to guard against them Understand how AI works for you and with you Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Azure AI Services at Scale for Cloud, Mobile, and Edge

Azure AI Services at Scale for Cloud, Mobile, and Edge PDF Author: Simon Bisson
Publisher: "O'Reilly Media, Inc."
ISBN: 1098107993
Category : Computers
Languages : en
Pages : 234

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Book Description
Take advantage of the power of cloud and the latest AI techniques. Whether you're an experienced developer wanting to improve your app with AI-powered features or you want to make a business process smarter by getting AI to do some of the work, this book's got you covered. Authors Anand Raman, Chris Hoder, Simon Bisson, and Mary Branscombe show you how to build practical intelligent applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. This book shows you how cloud AI services fit in alongside familiar software development approaches, walks you through key Microsoft AI services, and provides real-world examples of AI-oriented architectures that integrate different Azure AI services. All you need to get started is a working knowledge of basic cloud concepts. Become familiar with Azure AI offerings and capabilities Build intelligent applications using Azure Cognitive Services Train, tune, and deploy models with Azure Machine Learning, PyTorch, and the Open Neural Network Exchange (ONNX) Learn to solve business problems using AI in the Power Platform Use transfer learning to train vision, speech, and language models in minutes

Power Platform and the AI Revolution

Power Platform and the AI Revolution PDF Author: Aaron Guilmette
Publisher: Packt Publishing Ltd
ISBN: 1835089925
Category : Computers
Languages : en
Pages : 356

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Book Description
Unlock the untapped potential of ChatGPT, CoPilot, and Azure AI services by integrating them with the Microsoft Power Platform Key Features Gain insights into the latest AI technologies and their business applications Use generative AI to build apps, workflows, and chatbots Learn how to integrate AI services to automate work and deliver apps for specific business needs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn this AI era, employing leading machine learning and AI models such as ChatGPT for responding to customer feedback and prototyping applications is crucial to drive business success in the competitive market. This book is an indispensable guide to integrating cutting-edge technology into business operations and leveraging AI to analyze sentiment at scale, helping free up valuable time to enhance customer relationships. Immerse yourself in the future of AI-enabled application development by working with Power Automate, Power Apps, and the new Copilot Studio. With this book, you’ll learn foundational AI concepts as you explore the extensive capabilities of the low-code Power Platform. You’ll see how Microsoft's advanced machine learning technologies can streamline common business tasks such as extracting key data elements from customer documents, reviewing customer emails, and validating passports and drivers’ licenses. The book also guides you in harnessing the power of generative AI to expedite tasks like creating executive summaries, building presentations, and analyzing resumes. You’ll build apps using natural language prompting and see how ChatGPT can be used to power chatbots in your organization. By the end of this book, you’ll have charted your path to developing your own reusable AI automation patterns to propel your business operations into the future.What you will learn Interact with ChatGPT using connectors and HTTP calls Train AI models to identify the key elements of documents Use generative AI to answer questions about organizational content Leverage AI image recognition services to describe pictures Use generative AI tools to help build workflows and apps Build chatbots using the new Copilot Studio Analyze customer feedback using AI sentiment analysis tools such as AI Builder Who this book is for If you’re interested in exploring the capabilities of modern AI technologies in the workplace, this book is for you. Specially tailored for IT professionals, developers, business leaders, human resources administrators, managers, and entrepreneurs–anyone aspiring to become a productivity rockstar will find this book helpful for extending their skill set through hands-on exercises. The content is beginner-friendly, assuming no knowledge of machine learning or artificial intelligence concepts, making it a perfect starting point for newcomers to the field.