Grokking Machine Learning
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Grokking Machine Learning
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Narrado por:
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Marianne Sheehan
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De:
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Luis Serrano
Acerca de esta escucha
Discover valuable machine learning techniques you can understand and apply using just high school math.
In Grokking Machine Learning, you will learn:
- Supervised algorithms for classifying and splitting data
- Methods for cleaning and simplifying data
- Machine learning packages and tools
- Neural networks and ensemble methods for complex datasets
Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math. No specialist knowledge is required to tackle the hands-on exercises using Python and readily available machine learning tools. Packed with easy-to-follow Python-based exercises and mini-projects, this book sets you on the path to becoming a machine learning expert.
About the technology
Discover powerful machine learning techniques you can understand and apply using only high school math! Put simply, machine learning is a set of techniques for data analysis based on algorithms that deliver better results as you give them more data. ML powers many cutting-edge technologies, such as recommendation systems, facial recognition software, smart speakers, and even self-driving cars. This unique book introduces the core concepts of machine learning, using relatable examples, engaging exercises, and crisp illustrations.
About the book
Grokking Machine Learning presents machine learning algorithms and techniques in a way that anyone can understand. This book skips the confused academic jargon and offers clear explanations that require only basic algebra. As you go, you’ll build interesting projects with Python, including models for spam detection and image recognition. You’ll also pick up practical skills for cleaning and preparing data.
About the listener
For listeners who know basic Python. No machine learning knowledge necessary.
About the author
Luis G. Serrano is a research scientist in quantum artificial intelligence. Previously, he was an ML Engineer at Google and Lead AI Educator at Apple.
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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De: Laurence Moroney
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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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General3 out of 5 stars 5
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Narración:2 out of 5 stars 4
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Historia2 out of 5 stars 4
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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3 out of 5 stars
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Hard to follow when every other sentence “see code”. Some books don’t convey well in audio
- De Michael Little en 03-13-25
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Machine Learning Bookcamp
- Build a Portfolio of Real-Life Projects
- De: Alexey Grigorev
- Narrado por: Adam Newmark
- Duración: 8 h y 49 m
- Versión completa
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General5 out of 5 stars 2
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Narración:5 out of 5 stars 2
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Historia4.5 out of 5 stars 2
In Machine Learning Bookcamp, you’ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image analysis, each new project builds on what you’ve learned in previous chapters. You’ll build a portfolio of business-relevant machine learning projects that hiring managers will be excited to see.
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5 out of 5 stars
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Good but I mixed ebook + audio book
- De JUAN CARLOS MARTINEZ LOERA en 10-27-24
De: Alexey Grigorev
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The Complete Software Developer's Career Guide
- How to Learn Programming Languages Quickly, Ace Your Programming Interview, and Land Your Software Developer Dream Job
- De: John Sonmez
- Narrado por: John Sonmez
- Duración: 20 h y 4 m
- Versión completa
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General4.5 out of 5 stars 1,019
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Narración:4.5 out of 5 stars 891
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Historia4.5 out of 5 stars 879
Technical knowledge alone isn't enough - increase your software development income by leveling up your soft skills Early in his software developer career, John Sonmez discovered that technical knowledge alone isn't enough to break through to the next income level - developers need "soft skills" like the ability to learn new technologies just in time, communicate clearly with management and consulting clients, negotiate a fair hourly rate, and unite teammates and coworkers in working toward a common goal.
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2 out of 5 stars
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The Complete Bro-grammer's Career Guide
- De Leels en 09-18-19
De: John Sonmez
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Grokking Simplicity: Taming Complex Software with Functional Thinking
- De: Eric Normand
- Narrado por: Mark Thomas
- Duración: 12 h y 4 m
- Versión completa
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General3.5 out of 5 stars 12
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Narración:4 out of 5 stars 10
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Historia4 out of 5 stars 10
Grokking Simplicity is a friendly, practical guide that will change the way you approach software design and development. Distributed across servers, difficult to test, and resistant to modification - modern software is complex. Grokking Simplicity is a friendly, practical guide that will change the way you approach software design and development. It introduces a unique approach to functional programming that explains why certain features of software are prone to complexity, and teaches you the functional techniques you can use to simplify these systems.
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2 out of 5 stars
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Good book but not for audio format
- De Daniel Underwood en 07-22-23
De: Eric Normand
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Why Machines Learn
- The Elegant Math Behind Modern AI
- De: Anil Ananthaswamy
- Narrado por: Rene Ruiz
- Duración: 13 h y 30 m
- Versión completa
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General4.5 out of 5 stars 27
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Narración:4.5 out of 5 stars 26
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Historia4.5 out of 5 stars 26
We are living through a revolution in machine learning-powered AI that shows no signs of slowing down. This technology is based on relatively simple mathematical ideas, some of which go back centuries, including linear algebra and calculus, the stuff of seventeenth- and eighteenth-century mathematics. It took the birth and advancement of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see today. In this enlightening book, Anil Ananthaswamy explains the fundamental math behind machine learning.
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5 out of 5 stars
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A great listen, but a physical book is pre appropriate
- De Sameer D. en 11-07-24
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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 5
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Narración:4.5 out of 5 stars 5
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Historia4.5 out of 5 stars 5
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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Clean Code
- A Handbook of Agile Software Craftsmanship
- De: Robert C. Martin
- Narrado por: Theodore O'Brien
- Duración: 5 h y 49 m
- Versión completa
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General4.5 out of 5 stars 320
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Narración:5 out of 5 stars 233
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Historia4.5 out of 5 stars 229
Noted software expert Robert C. Martin presents a revolutionary paradigm with Clean Code: A Handbook of Agile Software Craftsmanship. Martin has teamed up with his colleagues from Object Mentor to distill their best agile practice of cleaning code “on the fly” into a book that will instill within you the values of a software craftsman and make you a better programmer - but only if you work at it.
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3 out of 5 stars
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Quick fix needed
- De R L en 05-06-21
De: Robert C. Martin
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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 17
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Narración:4.5 out of 5 stars 14
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Historia4 out of 5 stars 14
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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The Master Algorithm
- How the Quest for the Ultimate Learning Machine Will Remake Our World
- De: Pedro Domingos
- Narrado por: Mel Foster
- Duración: 13 h y 3 m
- Versión completa
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General4.5 out of 5 stars 1,677
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Narración:4.5 out of 5 stars 1,432
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Historia4.5 out of 5 stars 1,426
Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.
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4 out of 5 stars
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Great book, irritating narration
- De N. G. PEPIN en 09-24-15
De: Pedro Domingos
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Modern Software Engineering
- Doing What Works to Build Better Software Faster
- De: David Farley
- Narrado por: Amy Gordon
- Duración: 9 h y 37 m
- Versión completa
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General4.5 out of 5 stars 113
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Narración:4.5 out of 5 stars 92
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Historia4.5 out of 5 stars 92
In Modern Software Engineering, continuous delivery pioneer David Farley helps software professionals think about their work more effectively, manage it more successfully, and genuinely improve the quality of their applications, their lives, and the lives of their colleagues.
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3 out of 5 stars
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Could have been a 1-page bulleted list
- De Elle7se en 12-30-22
De: David Farley
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The Pragmatic Programmer: 20th Anniversary Edition, 2nd Edition
- Your Journey to Mastery
- De: David Thomas, Andrew Hunt
- Narrado por: Anna Katarina
- Duración: 9 h y 55 m
- Versión completa
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General4.5 out of 5 stars 1,582
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Narración:5 out of 5 stars 1,282
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Historia4.5 out of 5 stars 1,264
Dave Thomas and Andy Hunt wrote the first edition of this influential book in 1999 to help their clients create better software and rediscover the joy of coding. These lessons have helped a generation of programmers examine the very essence of software development. Now, 20 years later, this new edition re-examines what it means to be a modern programmer. Topics range from personal responsibility and career development to architectural techniques for keeping your code flexible and easy to adapt and reuse.
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5 out of 5 stars
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An excellent and entertaining technical book
- De Amazon Customer en 01-21-20
De: David Thomas, y otros
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AI at the Edge
- Solving Real-World Problems with Embedded Machine Learning
- De: Daniel Situnayake, Jenny Plunkett
- Narrado por: Suzie Althens
- Duración: 17 h y 17 m
- Versión completa
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General4 out of 5 stars 4
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Narración:5 out of 5 stars 3
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Historia5 out of 5 stars 3
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.
De: Daniel Situnayake, y otros
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Artificial Intelligence
- A Guide for Thinking Humans
- De: Melanie Mitchell
- Narrado por: Abby Craden, Melanie Mitchell, Tony Wolf
- Duración: 9 h y 33 m
- Versión completa
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General4.5 out of 5 stars 414
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Narración:4.5 out of 5 stars 351
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Historia4.5 out of 5 stars 349
In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent - really - are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant methods of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought that led to recent achievements.
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5 out of 5 stars
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Start understanding AI right here!
- De Chad M. en 01-26-20
De: Melanie Mitchell
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Algorithms to Live By
- The Computer Science of Human Decisions
- De: Brian Christian, Tom Griffiths
- Narrado por: Brian Christian
- Duración: 11 h y 50 m
- Versión completa
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General4.5 out of 5 stars 17,379
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Narración:4.5 out of 5 stars 14,663
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Historia4.5 out of 5 stars 14,547
From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.
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5 out of 5 stars
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Great listen, just don't expect tips!
- De Adam Hosman en 08-07-17
De: Brian Christian, y otros
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Designing Data-Intensive Applications
- The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
- De: Martin Kleppmann
- Narrado por: Benjamin Lange
- Duración: 20 h y 56 m
- Versión completa
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General5 out of 5 stars 450
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Narración:5 out of 5 stars 328
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Historia5 out of 5 stars 325
Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.
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5 out of 5 stars
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Must read for senior+ software engineers
- De Navid v en 05-29-21
De: Martin Kleppmann
Lo que los oyentes dicen sobre Grokking Machine Learning
Calificaciones medias de los clientesReseñas - Selecciona las pestañas a continuación para cambiar el origen de las reseñas.
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Total1 out of 5 stars
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Ejecución1 out of 5 stars
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Historia1 out of 5 stars
- Amazon Customer
- 04-05-24
Bad as an audiobook
Good info, terrible as an audiobook. Nothing more dull than hearing someone read formulas and code you can’t see.
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