
Machine Learning Interviews
Kickstart Your Machine Learning and Data Career
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Narrado por:
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Xifeng Brooks
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De:
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Susan Shu Chang
Acerca de esta escucha
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.
Having served as principal data scientist in several companies, Chang has considerable experience as both ML interviewer and interviewee. She'll take you through the highly selective recruitment process by sharing hard-won lessons she learned along the way. You'll quickly understand how to successfully navigate your way through typical ML interviews.
This guide shows you how to: explore various machine learning roles, including ML engineer, applied scientist, and data scientist; assess your interests and skills before deciding which ML role(s) to pursue; evaluate your current skills and close any gaps that may prevent you from succeeding in the interview process; acquire the skill set necessary for each machine learning role; ace ML interview topics, including coding assessments, statistics and machine learning theory, and behavioral questions; and prepare for interviews in statistics and machine learning theory by studying common interview questions.
PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
©2024 Quill Game Studios Inc. o/a Quill Technologies (P)2024 Ascent AudioLos oyentes también disfrutaron...
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De: Aditya Bhargava
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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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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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Great for beginners to learn AI!
- De AmySP en 04-25-25
De: Jordan Blake
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Software Engineering at Google
- Lessons Learned from Programming Over Time
- De: Titus Winters, Tom Manshreck, Hyrum Wright
- Narrado por: Mark Sando
- Duración: 23 h y 36 m
- Versión completa
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How can software engineers manage a living codebase that evolves and responds to changing requirements and demands over the length of its life? Based on their experience at Google, software engineers Titus Winters and Hyrum Wright, along with technical writer Tom Manshreck, present a candid and insightful look at how some of the world’s leading practitioners construct and maintain software. This book covers Google’s unique engineering culture, processes, and tools and how these aspects contribute to the effectiveness of an engineering organization.
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not useful
- De Andreas Andersen en 07-21-21
De: Titus Winters, y otros
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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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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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The best data science manual ever written
- De Jordan en 08-29-24
De: Alex J. Gutman, y otros
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Fundamentals of Software Architecture
- An Engineering Approach
- De: Mark Richards, Neal Ford
- Narrado por: Benjamin Lange
- Duración: 13 h y 10 m
- Versión completa
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This book provides the first comprehensive overview of software architecture’s many aspects. Aspiring and existing architects alike will examine architectural characteristics, architectural patterns, component determination, diagramming and presenting architecture, evolutionary architecture, and many other topics. Mark Richards and Neal Ford—hands-on practitioners who have taught software architecture classes professionally for years—focus on architecture principles that apply across all technology stacks.
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Helpful but business-centric
- De A.N. en 03-25-21
De: Mark Richards, y otros
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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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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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Good but I mixed ebook + audio book
- De JUAN CARLOS MARTINEZ LOERA en 10-27-24
De: Alexey Grigorev
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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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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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Really hard to follow when everything is see code
- De Senthil Manick en 05-12-25
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Grokking Machine Learning
- De: Luis Serrano
- Narrado por: Marianne Sheehan
- Duración: 15 h y 1 m
- Versión completa
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Discover valuable machine learning techniques you can understand and apply using just high school math. 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.
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Bad as an audiobook
- De Amazon Customer en 04-05-24
De: Luis Serrano
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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
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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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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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Acing the System Design Interview
- De: Zhiyong Tan
- Narrado por: Julie Brierley
- Duración: 16 h y 53 m
- Versión completa
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The system design interview is one of the hardest challenges you'll face in the software engineering hiring process. This practical book gives you the insights, the skills, and the hands-on practice you need to ace the toughest system design interview questions and land the job and salary you want.
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AI generated
- De Amazons Customer en 07-17-24
De: Zhiyong Tan
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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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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
Great advice, and read well.
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