AI at the Edge
Solving Real-World Problems with Embedded Machine Learning
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AI at the Edge
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Narrado por:
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Suzie Althens
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Edge AI is transforming the way computers interact with the real world, allowing IoT devices to make decisions using the 99% of sensor data that was previously discarded due to cost, bandwidth, or power limitations. With techniques like embedded machine learning, developers can capture human intuition and deploy it to any target—from ultra-low power microcontrollers to embedded Linux devices.
This practical guide gives engineering professionals, including product managers and technology leaders, an end-to-end framework for solving real-world industrial, commercial, and scientific problems with edge AI. You'll explore every stage of the process, from data collection to model optimization to tuning and testing, as you learn how to design and support edge AI and embedded ML products. Edge AI is destined to become a standard tool for systems engineers. This high-level road map helps you get started.
In this book, you'll develop your expertise in AI and ML for edge devices; understand which projects are best solved with edge AI; explore key design patterns for edge AI apps; learn an iterative workflow for developing AI systems; build a team with the skills to solve real-world problems; and follow a responsible AI process to create effective products.
PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
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Historia5 out of 5 stars 1
As tech products become more prevalent today, the demand for machine learning professionals continues to grow. But the responsibilities and skill sets required of ML professionals still vary drastically from company to company, making the interview process difficult to predict. In this guide, data science leader Susan Shu Chang shows you how to tackle the ML hiring process. She'll take you through the highly selective recruitment process by sharing hard-won lessons she learned along the way.
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5 out of 5 stars
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Great advice, and read well.
- De Goodmann en 01-26-25
De: Susan Shu Chang
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Build a Large Language Model (From Scratch)
- De: Sebastian Raschka
- Narrado por: Julie Brierley
- Duración: 7 h y 40 m
- Versión completa
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General2.5 out of 5 stars 7
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Narración:2 out of 5 stars 6
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Historia1.5 out of 5 stars 6
In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks.
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1 out of 5 stars
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Really hard to follow when everything is see code
- De Senthil Manick en 05-12-25
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Designing Machine Learning Systems
- An Iterative Process for Production-Ready Applications
- De: Chip Huyen
- Narrado por: Kathleen Li
- Duración: 15 h
- Versión completa
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General0 out of 5 stars 0
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Narración:0 out of 5 stars 0
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Historia0 out of 5 stars 0
Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, cofounder of Claypot AI, considers each design decision in the context of how it can help your system as a whole achieve its objectives.
De: Chip Huyen
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The Kaggle Book
- Data Analysis and Machine Learning for Competitive Data Science
- De: Konrad Banachewicz, Luca Massaron
- Narrado por: Alex Freeman
- Duración: 12 h y 29 m
- Versión completa
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General4 out of 5 stars 9
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Narración:4 out of 5 stars 7
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Historia4.5 out of 5 stars 7
Millions of data enthusiasts from around the world compete on Kaggle, the most famous data science competition platform of them all. Participating in Kaggle competitions is a surefire way to improve your data analysis skills, network with an amazing community of data scientists, and gain valuable experience to help grow your career. The first audiobook of its kind, The Kaggle Book assembles in one place the techniques and skills you'll need for success in competitions, data science projects, and beyond.
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1 out of 5 stars
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Absolutely disastrous
- De D B B en 05-16-24
De: Konrad Banachewicz, y otros
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Deep Learning with Python (Second Edition)
- De: Francois Chollet
- Narrado por: Derek Dysart
- Duración: 15 h y 1 m
- Versión completa
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General4 out of 5 stars 16
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Narración:4.5 out of 5 stars 14
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Historia4.5 out of 5 stars 14
Deep Learning with Python (Second Edition) introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you’ll build your understanding through intuitive explanations and clear examples. You’ll quickly pick up the skills you need to start developing deep learning applications.
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1 out of 5 stars
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Audible version is useless - has no PDF
- De Jim en 03-04-22
De: Francois Chollet
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Fundamentals of Data Engineering
- Plan and Build Robust Data Systems
- De: Joe Reis, Matt Housley
- Narrado por: Adam Verner
- Duración: 17 h y 31 m
- Versión completa
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General4.5 out of 5 stars 41
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Narración:4.5 out of 5 stars 35
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Historia4.5 out of 5 stars 35
Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.
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5 out of 5 stars
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Great for Hands on Business owners
- De LmL en 08-14-24
De: Joe Reis, y otros
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Software Architecture: The Hard Parts
- Modern Trade-Off Analyses for Distributed Architectures
- De: Neal Ford, Mark Richards, Pramod Sadalage, y otros
- Narrado por: Dena Dahilig
- Duración: 12 h y 53 m
- Versión completa
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General4 out of 5 stars 19
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Narración:4.5 out of 5 stars 15
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Historia4 out of 5 stars 15
There are no easy decisions in software architecture. Instead, there are many hard parts—difficult problems or issues with no best practices—that force you to choose among various compromises. With this book, you'll learn how to think critically about the trade-offs involved with distributed architectures. Architecture veterans and practicing consultants Neal Ford, Mark Richards, Pramod Sadalage, and Zhamak Dehghani discuss strategies for choosing an appropriate architecture.
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3 out of 5 stars
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Great content. Terrible narration.
- De Alex en 12-16-23
De: Neal Ford, y otros
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Data Mesh
- Delivering Data-Driven Value at Scale
- De: Zhamak Dehghani
- Narrado por: Zura Johnson
- Duración: 14 h y 2 m
- Versión completa
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General4 out of 5 stars 10
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Narración:3.5 out of 5 stars 5
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Historia4 out of 5 stars 5
We're at an inflection point in data, where our data management solutions no longer match the complexity of organizations, the proliferation of data sources, and the scope of our aspirations to get value from data with AI and analytics. In this practical book, Zhamak Dehghani introduces data mesh, a decentralized sociotechnical paradigm drawn from modern distributed architecture that provides a new approach to sourcing, sharing, accessing, and managing analytical data at scale.
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2 out of 5 stars
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Better Reference Text than an audiobook
- De Amazon Customer en 05-25-25
De: Zhamak Dehghani
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Becoming a Data Head
- How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning
- De: Alex J. Gutman, Jordan Goldmeier
- Narrado por: Brian Arens
- Duración: 7 h y 41 m
- Versión completa
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General4 out of 5 stars 7
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Narración:4.5 out of 5 stars 6
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Historia4.5 out of 5 stars 6
Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently bingeable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.
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5 out of 5 stars
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The best data science manual ever written
- De Jordan en 08-29-24
De: Alex J. Gutman, y otros
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Building Microservices
- Designing Fine-Grained Systems
- De: Sam Newman
- Narrado por: Theodore O'Brien
- Duración: 21 h y 12 m
- Versión completa
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General5 out of 5 stars 105
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Narración:5 out of 5 stars 82
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Historia4.5 out of 5 stars 81
As organizations shift from monolithic applications to smaller, self-contained microservices, distributed systems have become more fine-grained. But developing these new systems brings its own host of problems. This expanded second edition takes a holistic view of topics that you need to consider when building, managing, and scaling microservices architectures. Through clear examples and practical advice, author Sam Newman gives everyone from architects and developers to testers and IT operators a firm grounding in the concepts.
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5 out of 5 stars
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Easy to Understand
- De Anonymous User en 04-27-22
De: Sam Newman
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Natural Language Processing in Action: Understanding, Analyzing, and Generating Text with Python
- De: Hobson Lane, Hannes Hapke, Cole Howard
- Narrado por: Mark Thomas
- Duración: 18 h y 29 m
- Versión completa
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General4 out of 5 stars 11
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Narración:4 out of 5 stars 9
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Historia4 out of 5 stars 8
Natural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions.
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1 out of 5 stars
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Don't Waste Your Money on the Audio Version
- De wayne kurtz en 12-11-23
De: Hobson Lane, y otros
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The Staff Engineer's Path
- A Guide for Individual Contributors Navigating Growth and Change
- De: Tanya Reilly
- Narrado por: Wendy Tremont King
- Duración: 13 h y 52 m
- Versión completa
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General4.5 out of 5 stars 70
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Narración:4.5 out of 5 stars 62
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Historia4.5 out of 5 stars 62
For years, companies have rewarded their most effective engineers with management positions. But treating management as the default path for an engineer with leadership ability doesn't serve the industry well—or the engineer. The staff engineer's path allows engineers to contribute at a high level as role models, driving big projects, determining technical strategy, and raising everyone's skills. This in-depth book shows you how to understand your role, manage your time, master strategic thinking, and set the standard for technical work.
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2 out of 5 stars
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Not for all engineers
- De Dan H en 05-27-24
De: Tanya Reilly
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The Essentials of AI Deep Learning and Neural Networks
- Beginner's Guide to Understanding Machine Learning and Building Advanced AI Skills in Minutes a Day
- De: Jordan Blake
- Narrado por: Susan Prater
- Duración: 4 h y 23 m
- Versión completa
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General5 out of 5 stars 50
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Narración:5 out of 5 stars 49
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Historia5 out of 5 stars 49
Unlock the Secrets of AI Deep Learning and Neural Networks: Empower Your Future in Minutes a Day! Ready to dive into the world of artificial intelligence, but don’t know where to start? Whether you're a student, developer, or curious learner, this book takes you on a journey to master deep learning concepts, demystify neural networks, and transform your skills into real-world impact—all at your own pace.
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5 out of 5 stars
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Great for beginners to learn AI!
- De AmySP en 04-25-25
De: Jordan Blake
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Grokking Algorithms
- De: Aditya Bhargava
- Narrado por: Derek Lettman
- Duración: 3 h y 46 m
- Versión completa
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General4.5 out of 5 stars 131
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Narración:4.5 out of 5 stars 107
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Historia4 out of 5 stars 105
This friendly guide teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. This accesible introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.
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1 out of 5 stars
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the book is not good in audio format
- De Anonymous User en 01-09-20
De: Aditya Bhargava
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Algorithms and Data Structures for Massive Datasets
- De: Dzejla Medjedovic, Emin Tahirovic
- Narrado por: Mark Thomas
- Duración: 9 h y 45 m
- Versión completa
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General3.5 out of 5 stars 2
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Narración:4 out of 5 stars 2
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Historia4 out of 5 stars 2
Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You’ll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data.
De: Dzejla Medjedovic, y otros