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Author: Somdip Dey
Publisher: Somdip Dey
ISBN:
Category : Computers
Languages : en
Pages : 70
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Book Description
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.
Author: Somdip Dey
Publisher: Somdip Dey
ISBN:
Category : Computers
Languages : en
Pages : 70
Get Book Here
Book Description
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.
Author: Somdip Dey
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
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.
Author: Binto George
Publisher: CSTrends LLP
ISBN: 1944708022
Category : Computers
Languages : en
Pages : 1
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Book Description
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.
Author: Mark Treveil
Publisher: "O'Reilly Media, Inc."
ISBN: 1098116429
Category : Computers
Languages : en
Pages : 163
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Book Description
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
Author: Miao, Fengchun
Publisher: UNESCO Publishing
ISBN: 9231004476
Category : Political Science
Languages : en
Pages : 50
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Book Description
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]
Author: Amy Jo Kim
Publisher: Gamethinking.IO
ISBN: 9780999788547
Category : Games
Languages : en
Pages : 214
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Book Description
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.
Author: David Fradin
Publisher: Spice Catalyst Media via PublishDrive
ISBN:
Category : Business & Economics
Languages : en
Pages : 233
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Book Description
Building Insanely Great Products: Some Products Fail, Many Succeed...This is their Story is dedicated to one goal: To help you learn how you can enhance the chances of product success and reduce product failure. Steve Jobs coined the term “Building Insanely Great Products” and this book with many real-life examples tells the story of what he meant by that phrase and how every organization can build insanely great products and services. Building Insanely Great Products covers the six keys to success, how to do market research, the importance of customer loyalty, innovation and design, using personas for development and not just marketing, determining the product’s value proposition, the correct way to prioritize product features, market sizing that works, market segmentation, product positioning, distribution strategy, product lifecycle framework and process, and the customer journey and digital transformation. As Steve Johnson, the grandfather of product management training says: “... we’ve learned that companies often don’t know why they succeed and why they fail. Many rely on luck; too many rely on “HIPPO”—the highest paid person's opinion. And if you don’t know why you succeed, you won’t know how to succeed again.
Author: Trevor Hastie
Publisher: Springer Science & Business Media
ISBN: 0387216065
Category : Mathematics
Languages : en
Pages : 545
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Book Description
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.
Author: Camille Fournier
Publisher: "O'Reilly Media, Inc."
ISBN: 1491973846
Category : Business & Economics
Languages : en
Pages : 187
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Book Description
Managing people is difficult wherever you work. But in the tech industry, where management is also a technical discipline, the learning curve can be brutal—especially when there are few tools, texts, and frameworks to help you. In this practical guide, author Camille Fournier (tech lead turned CTO) takes you through each stage in the journey from engineer to technical manager. From mentoring interns to working with senior staff, you’ll get actionable advice for approaching various obstacles in your path. This book is ideal whether you’re a new manager, a mentor, or a more experienced leader looking for fresh advice. Pick up this book and learn how to become a better manager and leader in your organization. Begin by exploring what you expect from a manager Understand what it takes to be a good mentor, and a good tech lead Learn how to manage individual members while remaining focused on the entire team Understand how to manage yourself and avoid common pitfalls that challenge many leaders Manage multiple teams and learn how to manage managers Learn how to build and bootstrap a unifying culture in teams
Author: Sebastian Raschka
Publisher: Packt Publishing Ltd
ISBN: 1783555149
Category : Computers
Languages : en
Pages : 455
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Book Description
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.
