인공지능

학습하고, 추론하며, 우리의 세계를 재편할 수 있는 지능형 기계를 통해 인류 문명의 다음 위대한 도약이 펼쳐지고 있습니다. 이 책들은 실용적 응용과 기술적 혁신부터 의식, 고용, 그리고 디지털 창조물과 함께하는 인류의 미래에 대한 깊은 질문에 이르기까지 인공지능의 놀라운 잠재력과 심오한 도전을 탐구합니다.

인공지능 도서 요약

Data Science from Scratch

저자: Joel Grus • 2015

Real understanding comes from building algorithms yourself, not calling libraries others wrote.

3.90

1,000+

🐍 Python For Data Science ⚙️ Algorithm Implementation 📊 Statistical Thinking 📐 Applied Linear Algebra 🤖 Machine Learning Basics

Data Science from Scratch

Real understanding comes from building algorithms yourself, not calling libraries others wrote.

저자: Joel Grus 2015 403 페이지

3.90

1,000+ 개의 평점

🐍 Python For Data Science ⚙️ Algorithm Implementation 📊 Statistical Thinking 📐 Applied Linear Algebra 🤖 Machine Learning Basics

Robot-Proof

저자: Joseph E. Aoun • 2017

AI does knowledge work. A degree that survives teaches creativity cultural agility and reinvention.

3.62

500+

🎓 Higher Education Reform 🤖 Future Of Work 🧠 Ai And Automation 🔄 Lifelong Learning 🛠️ Experiential Learning

Robot-Proof

AI does knowledge work. A degree that survives teaches creativity cultural agility and reinvention.

저자: Joseph E. Aoun 2017 216 페이지

3.62

500+ 개의 평점

🎓 Higher Education Reform 🤖 Future Of Work 🧠 Ai And Automation 🔄 Lifelong Learning 🛠️ Experiential Learning

The Eye of the Master

저자: Matteo Pasquinelli • 2023

AI was never about thinking machines. It was built to measure, rank, and control workers.

4.06

292

🧠 Critical AI Studies 💻 History Of Computing 🏭 Division Of Labor 🐝 Collective Intelligence 📏 Psychometric History

The Eye of the Master

AI was never about thinking machines. It was built to measure, rank, and control workers.

저자: Matteo Pasquinelli 2023 272 페이지

4.06

292 개의 평점

🧠 Critical AI Studies 💻 History Of Computing 🏭 Division Of Labor 🐝 Collective Intelligence 📏 Psychometric History

The AI Advantage

저자: Thomas H. Davenport • 2018

Stop chasing AI hype: the three business capabilities that actually deliver returns.

3.54

149

🏢 Enterprise Ai 📱 Digital Transformation ⚙️ Process Automation 🤝 Augmented Intelligence ⚖️ Responsible Ai

The AI Advantage

Stop chasing AI hype: the three business capabilities that actually deliver returns.

저자: Thomas H. Davenport 2018 248 페이지

3.54

149 개의 평점

🏢 Enterprise Ai 📱 Digital Transformation ⚙️ Process Automation 🤝 Augmented Intelligence ⚖️ Responsible Ai

Your Face Belongs to Us

저자: Kashmir Hill • 2023

A startup scraped 3 billion faces, sold the tool to police, and public anonymity may never recover.

4.11

2,000+

👤 Facial Recognition 🏢 Corporate Surveillance ⚖️ Algorithmic Bias 👁️ Surveillance Studies 📜 Privacy Law

Your Face Belongs to Us

A startup scraped 3 billion faces, sold the tool to police, and public anonymity may never recover.

저자: Kashmir Hill 2023 352 페이지

4.11

2,000+ 개의 평점

👤 Facial Recognition 🏢 Corporate Surveillance ⚖️ Algorithmic Bias 👁️ Surveillance Studies 📜 Privacy Law

AI for Educators

저자: Matt Miller • 2023

AI can write the essay. New assignments, saved hours, and a cheating standard that makes sense.

3.90

500+

🖥️ Classroom Technology 📚 Teaching Practice 🤖 Generative Ai 🧠 Ai Literacy 📝 Alternative Assessment

AI for Educators

AI can write the essay. New assignments, saved hours, and a cheating standard that makes sense.

저자: Matt Miller 2023 134 페이지

3.90

500+ 개의 평점

🖥️ Classroom Technology 📚 Teaching Practice 🤖 Generative Ai 🧠 Ai Literacy 📝 Alternative Assessment

Chat GPT For Fiction Writing

저자: Nova Leigh • 2023

How to make ChatGPT your fiction collaborator: from plot twists to final drafts.

4.40

116

🤖 Ai Writing Tools ✍️ Writing Craft Guides 🧠 Prompt Engineering 📖 Story Outlining 🧑‍🎤 Character Development

Chat GPT For Fiction Writing

How to make ChatGPT your fiction collaborator: from plot twists to final drafts.

저자: Nova Leigh 2023 116 페이지

4.40

116 개의 평점

🤖 Ai Writing Tools ✍️ Writing Craft Guides 🧠 Prompt Engineering 📖 Story Outlining 🧑‍🎤 Character Development

Human + Machine

저자: Paul R. Daugherty • 2018

AI won't replace workers. The real value is in the space where humans and machines collaborate.

3.62

500+

🏢 Ai In Business 🔄 Digital Transformation 🤝 Human-Ai Collaboration 🔮 Future Of Work 🛡️ Responsible Ai

Human + Machine

AI won't replace workers. The real value is in the space where humans and machines collaborate.

저자: Paul R. Daugherty 2018 246 페이지

3.62

500+ 개의 평점

🏢 Ai In Business 🔄 Digital Transformation 🤝 Human-Ai Collaboration 🔮 Future Of Work 🛡️ Responsible Ai

Deep Learning with Python

저자: François Chollet • 2017

The Keras creator teaches you to build neural networks that see, read, and create in Python.

4.57

1,000+

🧠 Deep Learning 🐍 Python Programming 🏋️ Model Training 👁️ Computer Vision 💬 Natural Language Processing

Deep Learning with Python

The Keras creator teaches you to build neural networks that see, read, and create in Python.

저자: François Chollet 2017 350 페이지

4.57

1,000+ 개의 평점

🧠 Deep Learning 🐍 Python Programming 🏋️ Model Training 👁️ Computer Vision 💬 Natural Language Processing

The Ethical Algorithm

저자: Michael Kearns • 2019

Algorithms don't do ethics by default. Making them fair takes math, and the math demands trade-offs.

4.10

500+

⚖️ Algorithmic Bias 🔒 Data Privacy 🤖 Ai Ethics 🎲 Game Theory 🔬 Reproducibility Crisis

The Ethical Algorithm

Algorithms don't do ethics by default. Making them fair takes math, and the math demands trade-offs.

저자: Michael Kearns 2019 230 페이지

4.10

500+ 개의 평점

⚖️ Algorithmic Bias 🔒 Data Privacy 🤖 Ai Ethics 🎲 Game Theory 🔬 Reproducibility Crisis

The Algorithmic Leader

저자: Mike Walsh • 2019

Stop competing with machines. Redesign the work so humans do what only humans can.

3.88

255

🔄 Digital Transformation 🤖 Ai Strategy 🔮 Future Of Work 💻 Technology Leadership 🧩 Computational Thinking

The Algorithmic Leader

Stop competing with machines. Redesign the work so humans do what only humans can.

저자: Mike Walsh 2019 256 페이지

3.88

255 개의 평점

🔄 Digital Transformation 🤖 Ai Strategy 🔮 Future Of Work 💻 Technology Leadership 🧩 Computational Thinking

Artificial Intelligence in Practice

저자: Bernard Marr • 2019

Robots patrol Walmart aisles. Netflix guesses your next watch. How 50 companies already run on AI.

3.41

251

🤖 Ai In Business 📋 Corporate Case Studies 🧠 Applied Machine Learning 📈 Predictive Analytics ⚙️ Automation

Artificial Intelligence in Practice

Robots patrol Walmart aisles. Netflix guesses your next watch. How 50 companies already run on AI.

저자: Bernard Marr 2019 366 페이지

3.41

251 개의 평점

🤖 Ai In Business 📋 Corporate Case Studies 🧠 Applied Machine Learning 📈 Predictive Analytics ⚙️ Automation

AI Agents in Action

저자: Micheal Lanham • 2025

Give your LLM tools, memory, and teammates: patterns for building autonomous agents that work.

3.10

🤖 Ai Agents 🧠 Llm Development 🐝 Multi-Agent Systems ⚙️ Ai Engineering ✍️ Prompt Engineering

AI Agents in Action

Give your LLM tools, memory, and teammates: patterns for building autonomous agents that work.

저자: Micheal Lanham 2025 344 페이지

3.10

78 개의 평점

🤖 Ai Agents 🧠 Llm Development 🐝 Multi-Agent Systems ⚙️ Ai Engineering ✍️ Prompt Engineering

T-Minus AI

저자: Michael Kanaan • 2020

AI will decide global power. The race has already started, and not everyone plays fair.

3.74

500+

🌐 Ai Geopolitics 🏁 Tech Arms Races 🇺🇸 Us China Rivalry 👁️ Digital Authoritarianism ⚔️ Ai And Warfare

T-Minus AI

AI will decide global power. The race has already started, and not everyone plays fair.

저자: Michael Kanaan 2020 304 페이지

3.74

500+ 개의 평점

🌐 Ai Geopolitics 🏁 Tech Arms Races 🇺🇸 Us China Rivalry 👁️ Digital Authoritarianism ⚔️ Ai And Warfare

The Fourth Age

저자: Byron Reese • 2018

Three technologies made humanity. The fourth could unmake the boundary between human and machine.

4.01

1,000+

🤖 Artificial Intelligence 🧠 Consciousness Studies 🎲 Free Will Debate ⚙️ History Of Technology 💼 Future Of Work

The Fourth Age

Three technologies made humanity. The fourth could unmake the boundary between human and machine.

저자: Byron Reese 2018 335 페이지

4.01

1,000+ 개의 평점

🤖 Artificial Intelligence 🧠 Consciousness Studies 🎲 Free Will Debate ⚙️ History Of Technology 💼 Future Of Work

Natural Language Processing with Transformers

저자: Lewis Tunstall • 2022

Build NLP applications with the open-source stack that turned transformer research practical.

4.39

211

🗣️ Natural Language Processing 🧠 Deep Learning 🤖 Transformers 🔄 Transfer Learning 🔧 Open Source Tools

Natural Language Processing with Transformers

Build NLP applications with the open-source stack that turned transformer research practical.

저자: Lewis Tunstall 2022 406 페이지

4.39

211 개의 평점

🗣️ Natural Language Processing 🧠 Deep Learning 🤖 Transformers 🔄 Transfer Learning 🔧 Open Source Tools

The AI Playbook

저자: Eric Siegel • 2024

How to get machine learning out of the lab: sell the operational improvement, not the algorithm.

3.98

127

🏢 Enterprise Technology 🤖 Applied Ai 🔄 Change Management 📊 Data Quality 📏 Model Evaluation

The AI Playbook

How to get machine learning out of the lab: sell the operational improvement, not the algorithm.

저자: Eric Siegel 2024 253 페이지

3.98

127 개의 평점

🏢 Enterprise Technology 🤖 Applied Ai 🔄 Change Management 📊 Data Quality 📏 Model Evaluation

⿻ 數位 Plurality

저자: E. Glen Weyl • 2024

Tech promised liberation but delivered surveillance and polarization. Taiwan found the off-ramp.

3.51

🗳️ Digital Democracy 🏛️ Civic Technology 🧠 Collective Intelligence 💰 Public Goods Funding 🆔 Digital Identity

⿻ 數位 Plurality

Tech promised liberation but delivered surveillance and polarization. Taiwan found the off-ramp.

저자: E. Glen Weyl 2024 584 페이지

3.51

47 개의 평점

🗳️ Digital Democracy 🏛️ Civic Technology 🧠 Collective Intelligence 💰 Public Goods Funding 🆔 Digital Identity

Digital Transformation

저자: Thomas M. Siebel • 2019

Corporate lifespans dropped from 60 years to 20. Four technologies determine who goes extinct.

3.87

500+

🏭 Digital Disruption 🔄 Organizational Change 👔 CEO Leadership 🤖 AI Strategy ⚔️ AI Arms Race

Digital Transformation

Corporate lifespans dropped from 60 years to 20. Four technologies determine who goes extinct.

저자: Thomas M. Siebel 2019 253 페이지

3.87

500+ 개의 평점

🏭 Digital Disruption 🔄 Organizational Change 👔 CEO Leadership 🤖 AI Strategy ⚔️ AI Arms Race

Artificial Intelligence For Dummies (For Dummies

저자: John Paul Mueller • 2018

AI is math, not magic. A plain-English guide to what machine learning can and cannot do.

3.41

242

🤖 Ai For Beginners 📖 Ai Literacy 🎯 Narrow Ai 🧠 Deep Learning ⚖️ Ai Ethics

Artificial Intelligence For Dummies (For Dummies

AI is math, not magic. A plain-English guide to what machine learning can and cannot do.

저자: John Paul Mueller 2018 368 페이지

3.41

242 개의 평점

🤖 Ai For Beginners 📖 Ai Literacy 🎯 Narrow Ai 🧠 Deep Learning ⚖️ Ai Ethics

Impromptu

저자: Reid Hoffman • 2023

AI won't replace you. But someone using it will. The solo thinker era is ending.

3.77

500+

🛠️ Applied Ai 💼 Future Of Work 🤝 Human Ai Collaboration ☀️ Technology Optimism 🧠 Augmented Intelligence

Impromptu

AI won't replace you. But someone using it will. The solo thinker era is ending.

저자: Reid Hoffman 2023 248 페이지

3.77

500+ 개의 평점

🛠️ Applied Ai 💼 Future Of Work 🤝 Human Ai Collaboration ☀️ Technology Optimism 🧠 Augmented Intelligence

Mind

저자: John Rogers Searle • 2004

Neither ghost nor computer: consciousness is a biological fact and its feel can't be explained away.

3.86

500+

🧠 Philosophy Of Mind 💡 Consciousness Studies 🎯 Intentionality 🔗 Mind-Body Problem 📚 Analytic Philosophy

Mind

Neither ghost nor computer: consciousness is a biological fact and its feel can't be explained away.

저자: John Rogers Searle 2004 224 페이지

3.86

500+ 개의 평점

🧠 Philosophy Of Mind 💡 Consciousness Studies 🎯 Intentionality 🔗 Mind-Body Problem 📚 Analytic Philosophy

Practical Statistics for Data Scientists

저자: Peter Bruce • 2020

The statistics data scientists actually use, from EDA to ensembles, with working R and Python code.

4.21

261

📊 Statistical Computing 🔍 Exploratory Data Analysis 📐 Statistical Inference 🔄 Resampling Methods 📈 Regression Modeling

Practical Statistics for Data Scientists

The statistics data scientists actually use, from EDA to ensembles, with working R and Python code.

저자: Peter Bruce 2020 360 페이지

4.21

261 개의 평점

📊 Statistical Computing 🔍 Exploratory Data Analysis 📐 Statistical Inference 🔄 Resampling Methods 📈 Regression Modeling

Futureproof

저자: Kevin Roose • 2021

Three traits make you AI-proof. Building them is a practice, not a talent.

3.94

2,000+

🔮 Future Of Work 💼 Career Resilience 🧠 Human Skills 📵 Tech Mindfulness 🌐 Ai And Society

Futureproof

Three traits make you AI-proof. Building them is a practice, not a talent.

저자: Kevin Roose 2021 250 페이지

3.94

2,000+ 개의 평점

🔮 Future Of Work 💼 Career Resilience 🧠 Human Skills 📵 Tech Mindfulness 🌐 Ai And Society

Game Changer

저자: Matthew Sadler • 2019

From scratch, AlphaZero taught itself chess in nine hours and played like a Romantic-era genius.

4.21

289

🤖 Computer Chess ♟️ Chess Strategy 🔁 Reinforcement Learning ⚔️ Attacking Play ♞ Piece Activity

Game Changer

From scratch, AlphaZero taught itself chess in nine hours and played like a Romantic-era genius.

저자: Matthew Sadler 2019 416 페이지

4.21

289 개의 평점

🤖 Computer Chess ♟️ Chess Strategy 🔁 Reinforcement Learning ⚔️ Attacking Play ♞ Piece Activity

린 AI

저자: 로밋 파텔 • 2020

AI can multiply your marketing experiments a hundredfold. The startup framework for doing it.

3.64

🚀 Growth Marketing 📈 Startup Scaling 🤖 AI In Business 🎯 Customer Acquisition 📊 Data-Driven Marketing

린 AI

AI can multiply your marketing experiments a hundredfold. The startup framework for doing it.

저자: 로밋 파텔 2020 234 페이지

3.64

36 개의 평점

🚀 Growth Marketing 📈 Startup Scaling 🤖 AI In Business 🎯 Customer Acquisition 📊 Data-Driven Marketing

The Future of the Professions

저자: Richard Susskind • 2015

The professions were built on a trade: exclusive knowledge for public trust. That trade is ending.

3.64

1,000+

💼 Professional Services 🔮 Future Of Work ⚡ Technology Disruption 🧠 Knowledge Economics 🤖 Automation

The Future of the Professions

The professions were built on a trade: exclusive knowledge for public trust. That trade is ending.

저자: Richard Susskind 2015 368 페이지

3.64

1,000+ 개의 평점

💼 Professional Services 🔮 Future Of Work ⚡ Technology Disruption 🧠 Knowledge Economics 🤖 Automation

The ChatGPT Ninja

저자: Neil Dagger • 2023

AI detectors are blocking your work. The prompt methods and free tools that get past them.

4.14

139

🛠️ Prompt Engineering 🧠 Generative Ai ⚖️ Ai Ethics ✍️ Writing With Ai 📰 Misinformation

The ChatGPT Ninja

AI detectors are blocking your work. The prompt methods and free tools that get past them.

저자: Neil Dagger 2023 114 페이지

4.14

139 개의 평점

🛠️ Prompt Engineering 🧠 Generative Ai ⚖️ Ai Ethics ✍️ Writing With Ai 📰 Misinformation

Architects of Intelligence

저자: Martin Ford • 2018

AI's builders say the real crisis isn't superintelligence but a labor market already fracturing.

4.07

500+

🧠 Deep Learning ⚖️ Ai Ethics 👷 Future Of Work 📉 Automation Economics 🤝 Human-Ai Collaboration

Architects of Intelligence

AI's builders say the real crisis isn't superintelligence but a labor market already fracturing.

저자: Martin Ford 2018 554 페이지

4.07

500+ 개의 평점

🧠 Deep Learning ⚖️ Ai Ethics 👷 Future Of Work 📉 Automation Economics 🤝 Human-Ai Collaboration

The Algorithm

저자: Hilke Schellmann • 2024

Why you should fear the algorithms that hire and fire: they're biased, unscientific, and watching.

3.84

429

🏢 AI In The Workplace 💼 Hiring Practices ⚖️ Algorithmic Bias 👀 Workplace Surveillance 🤖 AI Ethics

The Algorithm

Why you should fear the algorithms that hire and fire: they're biased, unscientific, and watching.

저자: Hilke Schellmann 2024 312 페이지

3.84

429 개의 평점

🏢 AI In The Workplace 💼 Hiring Practices ⚖️ Algorithmic Bias 👀 Workplace Surveillance 🤖 AI Ethics

Practical Time Series Analysis

저자: Aileen Nielsen • 2019

When ARIMA beats deep learning, and when it doesn't: the pipeline from cleaning to prediction.

3.77

📈 Time Series Analysis 🔧 Feature Engineering 🧹 Data Preparation ⚙️ Machine Learning Pipelines 📊 Statistical Learning

Practical Time Series Analysis

When ARIMA beats deep learning, and when it doesn't: the pipeline from cleaning to prediction.

저자: Aileen Nielsen 2019 497 페이지

3.77

64 개의 평점

📈 Time Series Analysis 🔧 Feature Engineering 🧹 Data Preparation ⚙️ Machine Learning Pipelines 📊 Statistical Learning

Tools and Weapons

저자: Brad Smith • 2019

Tech weaponized your data, your vote, your face. An insider's plan to take them back.

3.85

1,000+

🏛️ Tech Policy 🔒 Privacy Rights 🛡️ Cybersecurity 🤖 Ai Ethics 🌐 Digital Divide

Tools and Weapons

Tech weaponized your data, your vote, your face. An insider's plan to take them back.

저자: Brad Smith 2019 368 페이지

3.85

1,000+ 개의 평점

🏛️ Tech Policy 🔒 Privacy Rights 🛡️ Cybersecurity 🤖 Ai Ethics 🌐 Digital Divide

The Age of A.I. and Our Human Future

저자: Henry Kissinger • 2021

Old rules of knowledge, power, and war were built for humans. AI is rewriting them.

3.43

5,000+

🤖 Machine Learning 🌐 Tech Geopolitics ⚖️ Ai Ethics 🚀 Autonomous Weapons 🐽 Ai Governance

The Age of A.I. and Our Human Future

Old rules of knowledge, power, and war were built for humans. AI is rewriting them.

저자: Henry Kissinger 2021 205 페이지

3.43

5,000+ 개의 평점

🤖 Machine Learning 🌐 Tech Geopolitics ⚖️ Ai Ethics 🚀 Autonomous Weapons 🐽 Ai Governance

The Future of Work

저자: Darrell M. West • 2018

Automation threatens half of all jobs. Our safety nets were designed for a different economy.

3.47

203

🏭 Workforce Automation 📉 Job Displacement 🚗 Gig Economy 🪪 Social Safety Net ⚖️ Technology Policy

The Future of Work

Automation threatens half of all jobs. Our safety nets were designed for a different economy.

저자: Darrell M. West 2018 209 페이지

3.47

203 개의 평점

🏭 Workforce Automation 📉 Job Displacement 🚗 Gig Economy 🪪 Social Safety Net ⚖️ Technology Policy

AI 지원 프로그래밍

저자: 톰 타울리 • 2024

Turn English into production code. The tools and prompts that ship features in half the time.

3.21

🖥️ Software Development 📝 Prompt Engineering 🤖 Ai-Assisted Coding 🧠 Large Language Models ✨ Generative Ai

AI 지원 프로그래밍

Turn English into production code. The tools and prompts that ship features in half the time.

저자: 톰 타울리 2024 222 페이지

3.21

57 개의 평점

🖥️ Software Development 📝 Prompt Engineering 🤖 Ai-Assisted Coding 🧠 Large Language Models ✨ Generative Ai

Possible Minds

저자: John Brockman • 2019

Twenty-five thinkers on AI's biggest risks and the one design question that matters most.

3.77

500+

🤖 Ai Ethics ⚙️ Ai Alignment 🔄 Cybernetics 🤝 Human-Ai Interaction ⚖️ Algorithmic Bias

Possible Minds

Twenty-five thinkers on AI's biggest risks and the one design question that matters most.

저자: John Brockman 2019 320 페이지

3.77

500+ 개의 평점

🤖 Ai Ethics ⚙️ Ai Alignment 🔄 Cybernetics 🤝 Human-Ai Interaction ⚖️ Algorithmic Bias

Artificial Intelligence

저자: Harvard Business Review • 2019

Thirteen trillion dollars in AI-driven growth by 2030. The strategy for capturing it.

3.93

449

♟️ Ai Strategy 🤖 Machine Learning 🤝 Human-Ai Collaboration 🚀 Ai Adoption 👥 Workforce Transformation

Artificial Intelligence

Thirteen trillion dollars in AI-driven growth by 2030. The strategy for capturing it.

저자: Harvard Business Review 2019 182 페이지

3.93

449 개의 평점

♟️ Ai Strategy 🤖 Machine Learning 🤝 Human-Ai Collaboration 🚀 Ai Adoption 👥 Workforce Transformation

Code Dependent

저자: Madhumita Murgia • 2024

Behind every AI is an exploited, invisible workforce. A reporter traces the human supply chain.

4.03

3,000+

⚖️ Algorithmic Bias 🤖 Ai Ethics 👷 Digital Labor 👁️ Surveillance Capitalism 🛡️ Content Moderation

Code Dependent

Behind every AI is an exploited, invisible workforce. A reporter traces the human supply chain.

저자: Madhumita Murgia 2024 309 페이지

4.03

3,000+ 개의 평점

⚖️ Algorithmic Bias 🤖 Ai Ethics 👷 Digital Labor 👁️ Surveillance Capitalism 🛡️ Content Moderation

The Little Book of Deep Learning

저자: François Fleuret • 2023

The machinery of deep learning, compressed: gradient descent, backprop, and attention.

4.32

151

🧠 Deep Learning 🔧 Model Architectures ⚡ Hardware Acceleration 📚 Supervised Learning 🎨 Generative Models

The Little Book of Deep Learning

The machinery of deep learning, compressed: gradient descent, backprop, and attention.

저자: François Fleuret 2023 168 페이지

4.32

151 개의 평점

🧠 Deep Learning 🔧 Model Architectures ⚡ Hardware Acceleration 📚 Supervised Learning 🎨 Generative Models

Digital Empires

저자: Anu Bradford • 2023

Three powers are battling to govern the internet, and the prize is the future of democracy.

3.91

151

🌐 Internet Governance ⚖️ Regulatory Competition 🇨🇳 Techno-Nationalism 🔒 Data Privacy 🏛️ Political Economy

Digital Empires

Three powers are battling to govern the internet, and the prize is the future of democracy.

저자: Anu Bradford 2023 608 페이지

3.91

151 개의 평점

🌐 Internet Governance ⚖️ Regulatory Competition 🇨🇳 Techno-Nationalism 🔒 Data Privacy 🏛️ Political Economy

Build a Large Language Model

저자: Sebastian Raschka • 2025

Skip expensive pretraining. Build a working LLM from GPT-2 and teach it to follow instructions.

4.60

356

🧠 Large Language Models 🗣️ Natural Language Processing 🏗️ Transformer Architectures 🔄 Self-Supervised Learning 🎯 Model Fine-Tuning

Build a Large Language Model

Skip expensive pretraining. Build a working LLM from GPT-2 and teach it to follow instructions.

저자: Sebastian Raschka 2025 400 페이지

4.60

356 개의 평점

🧠 Large Language Models 🗣️ Natural Language Processing 🏗️ Transformer Architectures 🔄 Self-Supervised Learning 🎯 Model Fine-Tuning

The Mind’s I

저자: Douglas R. Hofstadter • 1981

Borges, Turing, a headless mystic: the anthology where the self dissolves one essay at a time.

4.15

5,000+

🧠 Philosophy Of Mind 👁️ Consciousness Studies 🤖 Artificial Intelligence 🔬 Cognitive Science 💭 Thought Experiments

The Mind’s I

Borges, Turing, a headless mystic: the anthology where the self dissolves one essay at a time.

저자: Douglas R. Hofstadter 1981 512 페이지

4.15

5,000+ 개의 평점

🧠 Philosophy Of Mind 👁️ Consciousness Studies 🤖 Artificial Intelligence 🔬 Cognitive Science 💭 Thought Experiments

Surviving AI

저자: Calum Chace • 2015

Superintelligence is coming. It could be the greatest thing or the last thing we ever build.

3.88

500+

🎯 Ai Alignment ☢️ Existential Risk 🧠 Superintelligence 💥 Singularity 💼 Future Of Work

Surviving AI

Superintelligence is coming. It could be the greatest thing or the last thing we ever build.

저자: Calum Chace 2015 303 페이지

3.88

500+ 개의 평점

🎯 Ai Alignment ☢️ Existential Risk 🧠 Superintelligence 💥 Singularity 💼 Future Of Work

Real World AI

저자: Alyssa Simpson Rochwerger • 2021

Bring AI into a real business without bias, drift, and wasted millions: the practical playbook.

4.01

🏢 Enterprise Ai 🎯 Ai Strategy ⚖️ Responsible Ai 📊 Data Governance ⚙️ Mlops

Real World AI

Bring AI into a real business without bias, drift, and wasted millions: the practical playbook.

저자: Alyssa Simpson Rochwerger 2021 145 페이지

4.01

88 개의 평점

🏢 Enterprise Ai 🎯 Ai Strategy ⚖️ Responsible Ai 📊 Data Governance ⚙️ Mlops

Machines of Loving Grace

저자: John Markoff • 2015

Silicon Valley split between replacing humans and upgrading them. The fight isn't over.

3.67

500+

🖥️ History Of Computing 🤖 Artificial Intelligence 🖱️ Human-Computer Interaction 🏭 Automation And Labor ⚖️ Ai Ethics

Machines of Loving Grace

Silicon Valley split between replacing humans and upgrading them. The fight isn't over.

저자: John Markoff 2015 400 페이지

3.67

500+ 개의 평점

🖥️ History Of Computing 🤖 Artificial Intelligence 🖱️ Human-Computer Interaction 🏭 Automation And Labor ⚖️ Ai Ethics

Artificial Intelligence

저자: Margaret A. Boden • 2018

What AI can do, what it can't, and why the difference is philosophy more than code.

3.29

388

🧠 Artificial Intelligence 🔬 Cognitive Science 💭 Philosophy Of Mind ⚡ The Singularity ⚖️ Ethics Of Ai

Artificial Intelligence

What AI can do, what it can't, and why the difference is philosophy more than code.

저자: Margaret A. Boden 2018 164 페이지

3.29

388 개의 평점

🧠 Artificial Intelligence 🔬 Cognitive Science 💭 Philosophy Of Mind ⚡ The Singularity ⚖️ Ethics Of Ai

Introduction to Machine Learning with Python

저자: Andreas C. Müller • 2015

Build models that generalize, not just memorize: a Python data scientist's guide.

4.33

500+

🤖 Applied Machine Learning 📊 Data Science 🏷️ Supervised Learning 🐍 Scikit-Learn 🔧 Feature Engineering

Introduction to Machine Learning with Python

Build models that generalize, not just memorize: a Python data scientist's guide.

저자: Andreas C. Müller 2015 400 페이지

4.33

500+ 개의 평점

🤖 Applied Machine Learning 📊 Data Science 🏷️ Supervised Learning 🐍 Scikit-Learn 🔧 Feature Engineering

Machine Learning For Absolute Beginners

저자: Oliver Theobald • 2017

How machine learning algorithms think, from regression to neural networks, no math required.

4.12

474

🧠 Machine Learning 🧹 Data Preparation ⚖️ Model Evaluation 🏷️ Supervised Learning 🌳 Decision Trees

Machine Learning For Absolute Beginners

How machine learning algorithms think, from regression to neural networks, no math required.

저자: Oliver Theobald 2017 168 페이지

4.12

474 개의 평점

🧠 Machine Learning 🧹 Data Preparation ⚖️ Model Evaluation 🏷️ Supervised Learning 🌳 Decision Trees

What To Do When Machines Do Everything

저자: Malcolm Frank • 2017

12% of jobs vanish, 75% transform. AI's future is a build-out, not a takeover.

3.56

500+

⚙️ Digital Transformation 🏭 Industry 4.0 🤖 Ai In Business 🧑‍💻 Future Of Work 📊 Automation Economics

What To Do When Machines Do Everything

12% of jobs vanish, 75% transform. AI's future is a build-out, not a takeover.

저자: Malcolm Frank 2017 225 페이지

3.56

500+ 개의 평점

⚙️ Digital Transformation 🏭 Industry 4.0 🤖 Ai In Business 🧑‍💻 Future Of Work 📊 Automation Economics

Agentic Artificial Intelligence

저자: Pascal Bornet • 2025

Generative AI answers. Agentic AI acts. The gap between them is where business will be remade.

3.91

375

🏢 Enterprise Ai 🤖 Autonomous Systems ⚙️ Workforce Automation 🤝 Human-Ai Collaboration 🐝 Multi-Agent Systems

Agentic Artificial Intelligence

Generative AI answers. Agentic AI acts. The gap between them is where business will be remade.

저자: Pascal Bornet 2025 572 페이지

3.91

375 개의 평점

🏢 Enterprise Ai 🤖 Autonomous Systems ⚙️ Workforce Automation 🤝 Human-Ai Collaboration 🐝 Multi-Agent Systems

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