Low Code Ai


Low Code Ai
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Low Code Ai


Low Code Ai
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Author : Gwendolyn Stripling
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-09-13

Low Code Ai written by Gwendolyn Stripling and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-13 with Computers categories.


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
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Author : Gwendolyn Stripling
language : en
Publisher: O'Reilly Media
Release Date : 2023-10-31

Low Code Ai written by Gwendolyn Stripling and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-31 with Computers categories.


Take a data-first and use-case driven approach to understanding machine learning and deep learning concepts with Low-Code AI. This hands-on guide presents three problem-focused ways to learn ML: no code using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. 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 structured and unstructured data and understand the different 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 machine learning 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
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Author : Gwendolyn Stripling
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-09-13

Low Code Ai written by Gwendolyn Stripling and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-13 with Computers categories.


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



No Code Artificial Intelligence


No Code Artificial Intelligence
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Author : Ambuj Agrawal
language : en
Publisher: BPB Publications
Release Date : 2023-03-07

No Code Artificial Intelligence written by Ambuj Agrawal and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-07 with Computers categories.


A practical guide that will help you build AI and ML solutions faster with fewer efforts and no programming knowledge KEY FEATURES ● Start your journey to become an AI expert today. ● Learn how to build AI solutions to solve complex problems in your organization. ● Get familiar with different No-code AI tools and platforms. DESCRIPTION “No-Code Artificial Intelligence” is a book that enables you to develop AI applications without any programming knowledge. Authored by the founder of AICromo (https://aicromo.com/), this book takes you through an array of examples that shows how to build AI solutions using No-code AI tools. The book starts by sharing insights on the evolution of No-code AI and the different types of No-code AI tools and platforms available in the market. The book then helps you start building applications of Machine Learning in Finance, Healthcare, Sales, and Cybersecurity. It will also teach you to create AI applications to perform sales forecasting, find fraudulent claims, and detect diseases in plants. Furthermore, the book will show how to build Machine Learning models for a variety of use cases in image recognition, video object recognition, and data prediction. After reading this book, you will be able to build AI applications with ease. WHAT YOU WILL LEARN ● Use different No-code AI tools such as AWS Sagemaker, DataRobot, and Google AutoML. ● Learn how to create a Machine Learning model to predict housing prices. ● Build Natural Language Processing (NLP) models for Healthcare information Identification. ● Learn how to build an AI model to create targeted customer offerings. ● Use traditional ways to perform AI implementation using programming languages and AI libraries. WHO THIS BOOK IS FOR This book is for anyone who wants to build an AI app without writing any code. It is also helpful for current and aspiring AI and Machine Learning professionals who are looking to build automated, intelligent, and smart AI-based solutions. TABLE OF CONTENTS 1. What is AI? 2. Getting Started with No-Code AI 3. Building AI Model to Predict Housing Prices 4. Classifying Different Images 5. Building AI Model to Perform Sales Forecasting 6. Building AI Model to Find Fraudulent Claims 7. Building AI Model to Detect Diseases in Plants 8. Building AI Model to Create Targeted Customer Offerings 9. Building AI Model for Healthcare Information Identification 10. Building AI Model for Video Action Recognition 11. Building AI Applications with Coded AI



Ai Assisted Programming


Ai Assisted Programming
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Author : Tom Taulli
language : en
Publisher:
Release Date : 2024-05-21

Ai Assisted Programming written by Tom Taulli and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-21 with Computers categories.


Get practical advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, and design; coding; and debugging, testing, and documentation. With this practical book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs (ChatGPT, Bard, 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, Bard, 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 making chron jobs and GitHub Actions How to use AI-based low-code and no-code tools



Artificial Intelligence Basics


Artificial Intelligence Basics
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Author : Tom Taulli
language : en
Publisher: Apress
Release Date : 2019-08-01

Artificial Intelligence Basics written by Tom Taulli and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-01 with Computers categories.


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.



Beginning Azure Cognitive Services


Beginning Azure Cognitive Services
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Author : Alicia Moniz
language : en
Publisher: Apress
Release Date : 2021-09-01

Beginning Azure Cognitive Services written by Alicia Moniz and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-01 with Computers categories.


Get started with Azure Cognitive Services and its APIs that expose machine learning as a service. This book introduces the suite of Azure Cognitive Services and helps you take advantage of the proven machine learning algorithms that have been developed by experts and made available through Cognitive Services, easily integrating those algorithms into your own applications without having to develop the algorithms from scratch. The book also shows you how to use the algorithms provided by Cognitive Services to accelerate data analysis and development within your organization. The authors begin by introducing the tools and describing the steps needed to invoke libraries to analyze structured and unstructured text, speech, and pictures, and you will learn to create interactive chatbots using the Cognitive Services libraries. Each chapter contains the information you need to implement artificial intelligence (AI) via Azure Cognitive Services in your personal and professional projects. The book also covers ethical considerations that are becoming increasingly of concern when using AI to drive decision making. You will be introduced to tools such as FairLearn and InterpretML that can help you detect bias and understand the results your models are generating. What You Will Learn Invoke the Cognitive Services APIs from a variety of languages and apps Understand common design architectures for AI solutions in Azure Decrease discrimination and bias when creating an AI-driven solution Execute the examples within the book and learn how to extend those examples Implement best practices for leveraging the Vision, Speech, and Language parts of the suite Test Cognitive Services APIs via the Azure portal and using the Postman API tool Execute AI from low-code and no-code platforms like Logic Apps and Microsoft’s Power Platform Who This Book Is For Technical professionals who are interested in implementing artificial intelligence (AI) in pre-existing apps, expanding their value and skill sets, or learning more about AI for personal projects; for programmers working in languages such as C# and Python; and for those using low- and no-code platforms such as Microsoft Power Platform



The Ai Enabled Enterprise


The Ai Enabled Enterprise
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Author : Vinay Kulkarni
language : en
Publisher: Springer Nature
Release Date : 2023-12-17

The Ai Enabled Enterprise written by Vinay Kulkarni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-17 with Computers categories.


The AI enabled enterprise uses technology to continuously learn by monitoring its behavior and the environment as well as external knowledge sources in order to automate the decision-making and decision-implementation processes leading to continuous improvement over time. This book discusses the key challenges that organizations need to overcome in achieving an AI enabled enterprise: the role of digital twins in evidence-backed design, enterprise cartography that goes far beyond process mining, decision-making in the face of uncertainty, software architecture for continuous adaptation, democratized knowledge-guided software development enabling coordinated design, low code versus no code, and coherent design. For each challenge, the book proposes a line of attack along with the associated enabling technology and illustrates the same through a near real world use case.



Ai Assisted Programming


Ai Assisted Programming
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Author : Tom Taulli
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-04-10

Ai Assisted Programming written by Tom Taulli and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-10 with Computers categories.


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



Deep Learning For Coders With Fastai And Pytorch


Deep Learning For Coders With Fastai And Pytorch
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Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29

Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.


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