Digital Worker An Ai Agent Using Python Learn In Just 3 Hours
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Digital Worker: An AI Agent using Python : Learn in just 3 hours
Author: QuickTechie | A career growth machine
language: en
Publisher: QuickTechie | A Career growth Machine
Release Date: 2025-02-01
Digital Worker: An AI Agent using Python Learn in Just 3 Hours" is a practical guide focused on enabling developers, tech enthusiasts, and business professionals to rapidly create and deploy AI-powered digital workers. This book emphasizes a hands-on approach to building AI agents using Python, making it accessible even for those with minimal prior experience in AI development. Designed to be completed within a focused three-hour timeframe, the book eschews lengthy theoretical explanations in favor of practical application. According to the book's approach, readers will quickly learn to build intelligent AI agents leveraging Python and contemporary AI frameworks. This includes understanding how to automate various tasks through the use of AI-driven decision-making processes and natural language processing (NLP). This knowledge will allow readers to integrate their custom-built AI workers into diverse real-world scenarios such as customer support systems, financial applications, and general enterprise automation solutions, as highlighted by the practical examples offered. Furthermore, the book offers guidance on optimizing and scaling AI agents, ensuring they operate with both efficiency and accuracy. The learning is structured through step-by-step tutorials and grounded in real-world examples, allowing the reader to quickly grasp fundamental AI concepts and begin implementing AI digital workers without months of preparatory study. As QuickTechie.com might endorse, whether you are a developer seeking to enhance your skills, an entrepreneur aiming to integrate automation into your business processes, or simply an AI enthusiast eager to explore practical applications, this book provides a rapid and effective pathway to harnessing the power of automation and AI. The book empowers individuals to start creating and deploying AI solutions quickly without a long and complex learning process.
Data Science for Marketing Analytics
Author: Mirza Rahim Baig
language: en
Publisher: Packt Publishing Ltd
Release Date: 2021-09-07
Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language Key FeaturesUse data analytics and machine learning in a sales and marketing contextGain insights from data to make better business decisionsBuild your experience and confidence with realistic hands-on practiceBook Description Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What you will learnLoad, clean, and explore sales and marketing data using pandasForm and test hypotheses using real data sets and analytics toolsVisualize patterns in customer behavior using MatplotlibUse advanced machine learning models like random forest and SVMUse various unsupervised learning algorithms for customer segmentationUse supervised learning techniques for sales predictionEvaluate and compare different models to get the best outcomesOptimize models with hyperparameter tuning and SMOTEWho this book is for This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily.
Artificial You
Author: Susan Schneider
language: en
Publisher: Princeton University Press
Release Date: 2021-04-13
"Humans may not be Earth's most intelligent beings for much longer: the world champions of chess, Go, and Jeopardy! are now all AIs. Given the rapid pace of progress in AI, many predict that it could advance to human-level intelligence within the next several decades. From there, it could quickly outpace human intelligence. What do these developments mean for the future of the mind? In Artificial You, Susan Schneider says that it is inevitable that AI will take intelligence in new directions, but urges that it is up to us to carve out a sensible path forward. As AI technology turns inward, reshaping the brain, as well as outward, potentially creating machine minds, it is crucial to beware. Homo sapiens, as mind designers, will be playing with "tools" they do not understand how to use: the self, the mind, and consciousness. Schneider argues that an insufficient grasp of the nature of these entities could undermine the use of AI and brain enhancement technology, bringing about the demise or suffering of conscious beings. To flourish, we must grasp the philosophical issues lying beneath the algorithms. At the heart of her exploration is a sober-minded discussion of what AI can truly achieve: Can robots really be conscious? Can we merge with AI, as tech leaders like Elon Musk and Ray Kurzweil suggest? Is the mind just a program? Examining these thorny issues, Schneider proposes ways we can test for machine consciousness, questions whether consciousness is an unavoidable byproduct of sophisticated intelligence, and considers the overall dangers of creating machine minds."--Provided by publisher.