The Roadmap To Ai Mastery A Guide To Building And Scaling Projects

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The Roadmap to AI Mastery: A Guide to Building and Scaling Projects

Somdip Dey
The Roadmap to AI Mastery A Guide to Building and Scaling Projects Book PDF

Author : Somdip Dey
Publisher : Somdip Dey
Page : 70 pages
File Size : 55,9 Mb
Release : 2024-07-03
Category : Computers
ISBN : 8210379456XXX

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The Roadmap to AI Mastery: A Guide to Building and Scaling Projects by Somdip Dey Pdf

Are you a project or product manager or a tech enthusiast with little to no technical background in AI, but interested in harnessing the power of AI for your company's success? "The Roadmap to AI Mastery: A Guide to Building and Scaling Projects" is the perfect starting point for you. This practical guide, targeted towards project managers, product managers, and AI enthusiasts with non-technical backgrounds, covers everything from the introductory fundamentals of AI to selecting the right framework, creating AI models, overcoming common challenges, and more. Using real-world examples and a friendly tone, this book will help you gain introductory foundational understanding and confidence in building and scaling AI projects for your company's business goals. Don't wait to start your journey to AI mastery.

AI Mastery Trilogy

Andrew Hinton
AI Mastery Trilogy Book PDF

Author : Andrew Hinton
Publisher : Book Bound Studios
Page : 309 pages
File Size : 41,9 Mb
Release : 2024-07-03
Category : Business & Economics
ISBN : 9781761590078

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AI Mastery Trilogy by Andrew Hinton Pdf

Dive into the "AI Mastery Trilogy," the ultimate collection for professionals seeking to conquer the world of artificial intelligence (AI). This 3-in-1 compendium is meticulously crafted to guide you from the foundational principles of AI to the intricate mathematical frameworks and practical coding applications that will catapult your expertise to new heights. Book 1: "AI Basics for Managers" by Andrew Hinton is your gateway to understanding and implementing AI in business. It equips managers with the knowledge to navigate the AI landscape, identify opportunities, and lead their organizations toward a future of innovation and growth. Book 2: "Essential Math for AI" demystifies the mathematical backbone of AI, offering a deep dive into the core concepts that fuel AI systems. From linear algebra to game theory, this book is a treasure trove for anyone eager to grasp the numerical and logical foundations that underpin AI's transformative power. Book 3: "AI and ML for Coders" is the hands-on manual for coders ready to harness AI and machine learning in their projects. It provides a comprehensive overview of AI and ML technologies, practical coding advice, and ethical considerations, ensuring you're well-equipped to create cutting-edge, responsible AI applications. The "AI Mastery Trilogy" is more than just a set of books; it's a comprehensive learning journey designed to empower business leaders, mathematicians, and coders alike. Whether you're looking to lead, understand, or build the future of AI, this collection is an indispensable resource for mastering the art and science of one of the most exciting fields in technology. Embrace the AI revolution and secure your copy of the "AI Mastery Trilogy" today!

AI Product Management

Kumar Vishwesh
AI Product Management Book PDF

Author : Kumar Vishwesh
Publisher : Independently Published
Page : 0 pages
File Size : 52,6 Mb
Release : 2022-12-23
Category : Electronic
ISBN : 9798371006806

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AI Product Management by Kumar Vishwesh Pdf

Artificial intelligence (AI) is revolutionizing the way we do business, and AI product management is at the forefront of this transformation. In this practical guide, you'll learn the skills and strategies needed to successfully develop, launch, and scale AI products. We'll start by introducing you to the role of an AI product manager and the importance of AI in today's business landscape. From there, you'll learn how to understand the AI ecosystem and identify the right use cases for your AI product. You'll also discover how to build and manage an interdisciplinary team, design and develop an AI product, and launch and market it effectively. Throughout the book, you'll find real-world examples and best practices for growing and scaling your AI product. Whether you're a product manager, engineer, data scientist, or entrepreneur, this book will provide you with the knowledge and tools you need to succeed in the exciting field of AI product management. Key topics covered include: Understanding the AI landscape and key players Developing an AI product roadmap Building and managing an AI product team Designing and developing an AI product Launching and marketing an AI product Growing and scaling an AI product"

MLOps Explained

Louie Hawking
MLOps Explained Book PDF

Author : Louie Hawking
Publisher : Independently Published
Page : 0 pages
File Size : 51,5 Mb
Release : 2023-03-28
Category : Electronic
ISBN : 9798388983817

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MLOps Explained by Louie Hawking Pdf

"Revolutionize your AI projects with cutting-edge MLOps strategies." "Unleash the full potential of AI with MLOps mastery." "The essential blueprint for AI-driven innovation" _______________ Learn to unlock the true potential of machine learning in modern enterprises. This is your comprehensive roadmap to mastering MLOps, the groundbreaking discipline that bridges the gap between data science and software engineering. Unravel the secrets behind seamless collaboration, efficient workflows, and high-impact AI-driven solutions as you delve into the world of MLOps. Learn best practices for integrating machine learning models into your software pipeline, optimizing model deployment, and monitoring performance in real-time. With expert insights, practical tools, and cutting-edge techniques, "ML Ops Explained: The Art of Scaling AI" is an indispensable resource for software engineers, data scientists, and IT managers alike. Get ready to transform the way you build, deploy, and maintain AI-powered solutions with this essential guide, and scale your AI projects to new heights! _______________ Topics covered include: Building end-to-end AI pipelines: From data collection to model deployment. Addressing hidden technical debt in machine learning systems Automated testing and validation for machine learning models Performance metrics, data drift, and A/B testing. Future trends and challenges for MLOps and DevOps

Introducing MLOps

Mark Treveil,Nicolas Omont,Clément Stenac,Kenji Lefevre,Du Phan,Joachim Zentici,Adrien Lavoillotte,Makoto Miyazaki,Lynn Heidmann
Introducing MLOps Book PDF

Author : Mark Treveil,Nicolas Omont,Clément Stenac,Kenji Lefevre,Du Phan,Joachim Zentici,Adrien Lavoillotte,Makoto Miyazaki,Lynn Heidmann
Publisher : O'Reilly Media
Page : 186 pages
File Size : 51,7 Mb
Release : 2020-11-30
Category : Computers
ISBN : 9781098116446

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Introducing MLOps by Mark Treveil,Nicolas Omont,Clément Stenac,Kenji Lefevre,Du Phan,Joachim Zentici,Adrien Lavoillotte,Makoto Miyazaki,Lynn Heidmann Pdf

More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout. This book helps you: Fulfill data science value by reducing friction throughout ML pipelines and workflows Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized

Artificial Intelligence Simplified

Binto George,Gail Carmichael
Artificial Intelligence Simplified Book PDF

Author : Binto George,Gail Carmichael
Publisher : CSTrends LLP
Page : 1 pages
File Size : 47,8 Mb
Release : 2016-01-08
Category : Computers
ISBN : 9781944708023

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Artificial Intelligence Simplified by Binto George,Gail Carmichael Pdf

The book introduces key Artificial Intelligence (AI) concepts in an easy-to-read format with examples and illustrations. A complex, long, overly mathematical textbook does not always serve the purpose of conveying the basic AI concepts to most people. Someone with basic knowledge in Computer Science can have a quick overview of AI (heuristic searches, genetic algorithms, expert systems, game trees, fuzzy expert systems, natural language processing, super intelligence, etc.) with everyday examples. If you are taking a basic AI course and find the traditional AI textbooks intimidating, you may choose this as a “bridge” book, or as an introductory textbook. For students, there is a lower priced edition (ISBN 978-1944708016) of the same book. Published by CSTrends LLP.

AI and education

Miao, Fengchun,Holmes, Wayne,Ronghuai Huang,Hui Zhang,UNESCO
AI and education Book PDF

Author : Miao, Fengchun,Holmes, Wayne,Ronghuai Huang,Hui Zhang,UNESCO
Publisher : UNESCO Publishing
Page : 50 pages
File Size : 42,6 Mb
Release : 2021-04-08
Category : Political Science
ISBN : 9789231004476

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AI and education by Miao, Fengchun,Holmes, Wayne,Ronghuai Huang,Hui Zhang,UNESCO Pdf

Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]

Start Finishing

Charlie Gilkey
Start Finishing Book PDF

Author : Charlie Gilkey
Publisher : Unknown
Page : 0 pages
File Size : 45,7 Mb
Release : 2022-02-15
Category : Business & Economics
ISBN : 9781683648635

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Start Finishing by Charlie Gilkey Pdf

Start Finishing provides a system for transforming your ideas into finished projects. Here you’ll learn to focus your effort, identify drag points and pitfalls, build a pack of supporters, and end with momentum to start finishing the life-changing projects that create the future you want to live in.

The DevOps Handbook

Gene Kim,Jez Humble,Patrick Debois,John Willis
The DevOps Handbook Book PDF

Author : Gene Kim,Jez Humble,Patrick Debois,John Willis
Publisher : IT Revolution
Page : 515 pages
File Size : 55,5 Mb
Release : 2016-10-06
Category : Business & Economics
ISBN : 9781942788072

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The DevOps Handbook by Gene Kim,Jez Humble,Patrick Debois,John Willis Pdf

Increase profitability, elevate work culture, and exceed productivity goals through DevOps practices. More than ever, the effective management of technology is critical for business competitiveness. For decades, technology leaders have struggled to balance agility, reliability, and security. The consequences of failure have never been greater―whether it's the healthcare.gov debacle, cardholder data breaches, or missing the boat with Big Data in the cloud. And yet, high performers using DevOps principles, such as Google, Amazon, Facebook, Etsy, and Netflix, are routinely and reliably deploying code into production hundreds, or even thousands, of times per day. Following in the footsteps of The Phoenix Project, The DevOps Handbook shows leaders how to replicate these incredible outcomes, by showing how to integrate Product Management, Development, QA, IT Operations, and Information Security to elevate your company and win in the marketplace.

The Elements of Statistical Learning

Trevor Hastie,Robert Tibshirani,Jerome Friedman
The Elements of Statistical Learning Book PDF

Author : Trevor Hastie,Robert Tibshirani,Jerome Friedman
Publisher : Springer Science & Business Media
Page : 545 pages
File Size : 54,6 Mb
Release : 2013-11-11
Category : Mathematics
ISBN : 9780387216065

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The Elements of Statistical Learning by Trevor Hastie,Robert Tibshirani,Jerome Friedman Pdf

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

Game Thinking

Amy Jo Kim,Raph Koster
Game Thinking Book PDF

Author : Amy Jo Kim,Raph Koster
Publisher : Gamethinking.IO
Page : 214 pages
File Size : 51,5 Mb
Release : 2018-05-25
Category : Games
ISBN : 099978854X

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Game Thinking by Amy Jo Kim,Raph Koster Pdf

During her time working on genre-defining games like The Sims, Rock Band, and Ultima Online, Amy Jo learned that customers stick with products that help them get better at something they care about, like playing an instrument or leading a team. Amy Jo has used her insights from gaming to help hundreds of companies like Netflix, Disney, The New York Times, Ubisoft and Happify innovate faster and smarter, and drive long-term engagement.

ADKAR

Jeff Hiatt
ADKAR Book PDF

Author : Jeff Hiatt
Publisher : Prosci
Page : 164 pages
File Size : 55,6 Mb
Release : 2006
Category : Forandringsledelse
ISBN : 1930885504

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ADKAR by Jeff Hiatt Pdf

In his first complete text on the ADKAR model, Jeff Hiatt explains the origin of the model and explores what drives each building block of ADKAR. Learn how to build awareness, create desire, develop knowledge, foster ability and reinforce changes in your organization. The ADKAR Model is changing how we think about managing the people side of change, and provides a powerful foundation to help you succeed at change.

Python Machine Learning

Sebastian Raschka
Python Machine Learning Book PDF

Author : Sebastian Raschka
Publisher : Packt Publishing Ltd
Page : 455 pages
File Size : 43,9 Mb
Release : 2015-09-23
Category : Computers
ISBN : 9781783555147

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Python Machine Learning by Sebastian Raschka Pdf

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

Deep Learning With Python

Jason Brownlee
Deep Learning With Python Book PDF

Author : Jason Brownlee
Publisher : Machine Learning Mastery
Page : 266 pages
File Size : 40,5 Mb
Release : 2016-05-13
Category : Computers
ISBN : 8210379456XXX

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Deep Learning With Python by Jason Brownlee Pdf

Deep learning is the most interesting and powerful machine learning technique right now. Top deep learning libraries are available on the Python ecosystem like Theano and TensorFlow. Tap into their power in a few lines of code using Keras, the best-of-breed applied deep learning library. In this Ebook, learn exactly how to get started and apply deep learning to your own machine learning projects.

Engineering DevOps

Marc Hornbeek
Engineering DevOps Book PDF

Author : Marc Hornbeek
Publisher : Bookbaby
Page : 400 pages
File Size : 43,7 Mb
Release : 2019-12-06
Category : Electronic
ISBN : 1543989616

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Engineering DevOps by Marc Hornbeek Pdf

This book is an engineering reference manual that explains "How to do DevOps?". It is targeted to people and organizations that are "doing DevOps" but not satisfied with the results that they are getting. There are plenty of books that describe different aspects of DevOps and customer user stories, but up until now there has not been a book that frames DevOps as an engineering problem with a step-by-step engineering solution and a clear list of recommended engineering practices to guide implementors. The step-by-step engineering prescriptions can be followed by leaders and practitioners to understand, assess, define, implement, operationalize, and evolve DevOps for their organization. The book provides a unique collection of engineering practices and solutions for DevOps. By confining the scope of the content of the book to the level of engineering practices, the content is applicable to the widest possible range of implementations. This book was born out of the author's desire to help others do DevOps, combined with a burning personal frustration. The frustration comes from hearing leaders and practitioners say, "We think we are doing DevOps, but we are not getting the business results we had expected." Engineering DevOps describes a strategic approach, applies engineering implementation discipline, and focuses operational expertise to define and accomplish specific goals for each leg of an organization's unique DevOps journey. This book guides the reader through a journey from defining an engineering strategy for DevOps to implementing The Three Ways of DevOps maturity using engineering practices: The First Way (called "Continuous Flow") to The Second Way (called "Continuous Feedback") and finally The Third Way (called "Continuous Improvement"). This book is intended to be a guide that will continue to be relevant over time as your specific DevOps and DevOps more generally evolves.