No-code Artificial Intelligence : The new way to build AI powered applications / Ambuj Agrawal.
Material type:
- 9789355513496
- Q336 .A373 2023
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Books | University of Kalba | Q336 .A373 2023 (Browse shelf(Opens below)) | Available | 00-1-384089 |
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PE1112.3 .H37 2024 English for everyone. Level 1 beginner / Course book. | PE1112.3 .J64 2016 English for everyone : course book. Level 3 intermediate / | KMV1710 .S273 2024 شرح قانون الإجراءات المدنية الإماراتي في ظل المرسوم بقانون اتحادي رقم (42) لسنة2022 / | Q336 .A373 2023 No-code Artificial Intelligence : The new way to build AI powered applications / | QA76.73.C153 J664 2020 C++ programming / | QA76.73.P98 G353 2022 Network Programming in Python : The Basic: A Detailed Guide to Python 3 Network Programming and Management / | QA76.9.D343 M344 2023 Data analytics / |
Includes bibliographical references and index.
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.
"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.
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