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Books like Python for Data Analysis

Confident Data Skills
by Kirill Eremenko • 2018
From messy data to clean insights to persuasive presentations: the process that lands the promotion.
4.12
211
📊 Data Science📖 Data Literacy🤖 Machine Learning Basics📈 Data Visualization🧹 Data Preparation
Confident Data Skills Summary
Confident Data Skills 95%
From messy data to clean insights to persuasive presentations: the process that lands the promotion.
by Kirill Eremenko 2018
4.12
211 ratings
📊 Data Science📖 Data Literacy🤖 Machine Learning Basics📈 Data Visualization🧹 Data Preparation
Predictive Analytics For Dummies
by Anasse Bari • 2013
A guide to building models that forecast, classify, and find hidden patterns, without a math degree.
3.74
111
📊 Data Science🔮 Predictive Modeling🐥 Beginner Guides🧹 Data Preparation🧩 Clustering
Predictive Analytics For Dummies Summary
Predictive Analytics For Dummies 94%
A guide to building models that forecast, classify, and find hidden patterns, without a math degree.
by Anasse Bari 2013
3.74
111 ratings
📊 Data Science🔮 Predictive Modeling🐥 Beginner Guides🧹 Data Preparation🧩 Clustering
Once Upon an Algorithm
by Martin Erwig • 2017
What Hansel and Gretel, Sherlock Holmes, and Groundhog Day can teach you about algorithms.
3.63
265
🧠 Computational Thinking📐 Algorithm Design📖 Story-Driven Education🔓 Accessible Algorithms🗄️ Data Structures
Once Upon an Algorithm Summary
Once Upon an Algorithm 94%
What Hansel and Gretel, Sherlock Holmes, and Groundhog Day can teach you about algorithms.
by Martin Erwig 2017
3.63
265 ratings
🧠 Computational Thinking📐 Algorithm Design📖 Story-Driven Education🔓 Accessible Algorithms🗄️ Data Structures
A Common-Sense Guide to Data Structures and Algorithms
by Jay Wengrow • 2017
The algorithm knowledge that turns working code into fast code, explained without the math degree.
4.39
603
🧱 Data Structures⏱️ Algorithm Analysis🧠 Algorithmic Thinking🔧 Practical Algorithms⚡ Performance Optimization
A Common-Sense Guide to Data Structures and Algorithms Summary
A Common-Sense Guide to Data Structures and Algorithms 94%
The algorithm knowledge that turns working code into fast code, explained without the math degree.
by Jay Wengrow 2017
4.39
603 ratings
🧱 Data Structures⏱️ Algorithm Analysis🧠 Algorithmic Thinking🔧 Practical Algorithms⚡ Performance Optimization
Numsense! Data Science for the Layman
by Annalyn Ng • 2017
Data science without the math: twelve techniques, what they do, and why intuition alone falls short.
4.14
622
🧠 Data Literacy🤖 Machine Learning Basics📈 Predictive Analytics📊 Data-Driven Decisions📘 Technical Primers
Numsense! Data Science for the Layman Summary
Numsense! Data Science for the Layman 94%
Data science without the math: twelve techniques, what they do, and why intuition alone falls short.
by Annalyn Ng 2017
4.14
622 ratings
🧠 Data Literacy🤖 Machine Learning Basics📈 Predictive Analytics📊 Data-Driven Decisions📘 Technical Primers
Data Science
by John D. Kelleher • 2018
Turning raw data into decisions requires a defined process, not just algorithms and statistics.
3.90
876
🔎 Data Mining🧭 Data Science Methodology📈 Predictive Modeling🧩 Unsupervised Learning⚖️ Data Ethics
Data Science Summary
Data Science 93%
Turning raw data into decisions requires a defined process, not just algorithms and statistics.
by John D. Kelleher 2018
3.90
876 ratings
🔎 Data Mining🧭 Data Science Methodology📈 Predictive Modeling🧩 Unsupervised Learning⚖️ Data Ethics
The Complete Software Developer's Career Guide
by John Sonmez • 2017
One language, one portfolio, one interview strategy: the sequence that turns learners into hires.
4.02
1k+
💼 Software Careers🚪 Breaking Into Tech🎯 Technical Interviews⌨️ Learning To Code🧪 Software Testing
The Complete Software Developer's Career Guide Summary
The Complete Software Developer's Career Guide 93%
One language, one portfolio, one interview strategy: the sequence that turns learners into hires.
by John Sonmez 2017
4.02
1k+ ratings
💼 Software Careers🚪 Breaking Into Tech🎯 Technical Interviews⌨️ Learning To Code🧪 Software Testing
14 Habits of Highly Productive Developers
by Zeno Rocha • 2020
Fourteen habits for developers who want to stop sprinting and start compounding.
4.00
723
🖥️ Software Engineering💼 Software Careers🧱 Code Craftsmanship📚 Continuous Learning📣 Learning In Public
14 Habits of Highly Productive Developers Summary
14 Habits of Highly Productive Developers 93%
Fourteen habits for developers who want to stop sprinting and start compounding.
by Zeno Rocha 2020
4.00
723 ratings
🖥️ Software Engineering💼 Software Careers🧱 Code Craftsmanship📚 Continuous Learning📣 Learning In Public
The Art of Doing Science and Engineering
by Richard W. Hamming • 1996
What separates great scientists from good ones: they pick better problems.
4.18
2k+
🧠 Scientific Thinking⚙️ Engineering Practice💻 Computational Thinking🔬 Research Methods🔗 Interdisciplinary
The Art of Doing Science and Engineering Summary
The Art of Doing Science and Engineering 93%
What separates great scientists from good ones: they pick better problems.
by Richard W. Hamming 1996
4.18
2k+ ratings
🧠 Scientific Thinking⚙️ Engineering Practice💻 Computational Thinking🔬 Research Methods🔗 Interdisciplinary
Machine Learning For Absolute Beginners
by 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 Summary
Machine Learning For Absolute Beginners 92%
How machine learning algorithms think, from regression to neural networks, no math required.
by Oliver Theobald 2017
4.12
474 ratings
🧠 Machine Learning🧹 Data Preparation⚖️ Model Evaluation🏷️ Supervised Learning🌳 Decision Trees
Clean Code in Python
by Mariano Anaya • 2018
Python decorators, descriptors, generators: most teams misuse them. Here is the clean way.
4.09
130
🐍 Python Programming🔨 Software Craftsmanship✅ Code Quality🪶 Pythonic Idioms🧱 Solid Principles
Clean Code in Python Summary
Clean Code in Python 92%
Python decorators, descriptors, generators: most teams misuse them. Here is the clean way.
by Mariano Anaya 2018
4.09
130 ratings
🐍 Python Programming🔨 Software Craftsmanship✅ Code Quality🪶 Pythonic Idioms🧱 Solid Principles
Clean Code
by Robert C. Martin • 2007
Unreadable code makes every change a gamble. The craft rules for code that stays maintainable.
4.35
24k+
🧹 Code Quality🛠️ Software Craftsmanship♻️ Refactoring🧪 Unit Testing🧩 Object-Oriented Design
Clean Code Summary
Clean Code 92%
Unreadable code makes every change a gamble. The craft rules for code that stays maintainable.
by Robert C. Martin 2007
4.35
24k+ ratings
🧹 Code Quality🛠️ Software Craftsmanship♻️ Refactoring🧪 Unit Testing🧩 Object-Oriented Design
Algorithms
by Panos Louridas • 2020
Twenty steps to find one item in a million, and the hidden logic that runs our world.
4.03
302
📐 Algorithm Design💻 Computing Primers🕸️ Graph Theory🔍 Search Algorithms📊 Data Sorting
Algorithms Summary
Algorithms 92%
Twenty steps to find one item in a million, and the hidden logic that runs our world.
by Panos Louridas 2020
4.03
302 ratings
📐 Algorithm Design💻 Computing Primers🕸️ Graph Theory🔍 Search Algorithms📊 Data Sorting
How to Speak Tech
by Vinay Trivedi • 2013
No coding required: the Internet, cloud, databases, and software, translated into business sense.
3.93
204
📖 Tech Literacy🌐 Web Development☁️ Cloud Computing🗄️ Database Management🔄 Agile Methodology
How to Speak Tech Summary
How to Speak Tech 92%
No coding required: the Internet, cloud, databases, and software, translated into business sense.
by Vinay Trivedi 2013
3.93
204 ratings
📖 Tech Literacy🌐 Web Development☁️ Cloud Computing🗄️ Database Management🔄 Agile Methodology
Nine Algorithms That Changed the Future
by John MacCormick • 2012
The hidden algorithms behind search and security, and the one problem no machine can solve.
3.89
2k+
📘 Algorithms Explained🧠 Computational Thinking🌐 Digital Infrastructure💻 How Computers Work🕰️ Computer Science History
Nine Algorithms That Changed the Future Summary
Nine Algorithms That Changed the Future 92%
The hidden algorithms behind search and security, and the one problem no machine can solve.
by John MacCormick 2012
3.89
2k+ ratings
📘 Algorithms Explained🧠 Computational Thinking🌐 Digital Infrastructure💻 How Computers Work🕰️ Computer Science History
Computational Thinking
by Peter J. Denning • 2019
It is a 4,500-year-old practice that built modern science, yet most confuse it with just coding.
3.63
304
💭 Computational Thinking🕰️ History Of Computing🎨 Design Thinking⚙️ Software Engineering🧠 Algorithmic Thinking
Computational Thinking Summary
Computational Thinking 92%
It is a 4,500-year-old practice that built modern science, yet most confuse it with just coding.
by Peter J. Denning 2019
3.63
304 ratings
💭 Computational Thinking🕰️ History Of Computing🎨 Design Thinking⚙️ Software Engineering🧠 Algorithmic Thinking
AI and Machine Learning for Coders
by Laurence Moroney • 2021
Turn your code into AI that runs everywhere: train, optimize, deploy with a single toolkit.
4.09
108
🤖 Machine Learning🧠 Deep Learning🔵 Tensorflow👁️ Computer Vision💬 Nlp
AI and Machine Learning for Coders Summary
AI and Machine Learning for Coders 92%
Turn your code into AI that runs everywhere: train, optimize, deploy with a single toolkit.
by Laurence Moroney 2021
4.09
108 ratings
🤖 Machine Learning🧠 Deep Learning🔵 Tensorflow👁️ Computer Vision💬 Nlp
The Clean Coder
by Robert C. Martin • 2011
A pro programmer's real job: saying no, keeping promises, staying calm when the build breaks.
4.26
9k+
💼 Developer Conduct🔨 Software Craftsmanship💎 Code Quality🧪 Automated Testing⏰ Time Management
The Clean Coder Summary
The Clean Coder 92%
A pro programmer's real job: saying no, keeping promises, staying calm when the build breaks.
by Robert C. Martin 2011
4.26
9k+ ratings
💼 Developer Conduct🔨 Software Craftsmanship💎 Code Quality🧪 Automated Testing⏰ Time Management
Code Complete
by Steve McConnell • 1993
Software construction eats 80 percent of project time and hides most defects. A disciplined craft.
4.30
9k+
📐 Software Engineering🔍 Code Quality🛡️ Defensive Programming⚒️ Software Craftsmanship🧩 Complexity Management
Code Complete Summary
Code Complete 92%
Software construction eats 80 percent of project time and hides most defects. A disciplined craft.
by Steve McConnell 1993
4.30
9k+ ratings
📐 Software Engineering🔍 Code Quality🛡️ Defensive Programming⚒️ Software Craftsmanship🧩 Complexity Management
Game Development Patterns and Best Practices
by John P. Doran • 2017
Design patterns that ship games: when to use each and how they prevent late-stage collapse.
3.90
20
🎮 Game Development🧩 Design Patterns🧹 Clean Code🏗️ Software Architecture⚡ Performance Optimization
Game Development Patterns and Best Practices Summary
Game Development Patterns and Best Practices 92%
Design patterns that ship games: when to use each and how they prevent late-stage collapse.
by John P. Doran 2017
3.90
20 ratings
🎮 Game Development🧩 Design Patterns🧹 Clean Code🏗️ Software Architecture⚡ Performance Optimization
Debugging
by David J. Agans • 2002
Learn to debug like a detective: reproduce the crime, divide the scene, and never guess.
4.26
509
🐛 Debugging🎯 Root Cause Analysis⚙️ Engineering Mindset🔧 Pragmatic Programming🧪 Scientific Method
Debugging Summary
Debugging 92%
Learn to debug like a detective: reproduce the crime, divide the scene, and never guess.
by David J. Agans 2002
4.26
509 ratings
🐛 Debugging🎯 Root Cause Analysis⚙️ Engineering Mindset🔧 Pragmatic Programming🧪 Scientific Method
Two Scoops of Django
by Daniel Roy Greenfeld • 2013
Django gets messy fast. The project structure, query rules, and Unix principle that keep it clean.
4.22
260
💻 Python Web Development🧩 Django Framework⚙️ Backend Development✨ Clean Code📁 Project Structure
Two Scoops of Django Summary
Two Scoops of Django 92%
Django gets messy fast. The project structure, query rules, and Unix principle that keep it clean.
by Daniel Roy Greenfeld 2013
4.22
260 ratings
💻 Python Web Development🧩 Django Framework⚙️ Backend Development✨ Clean Code📁 Project Structure
Becoming a Data Head
by Alex J. Gutman • 2021
The critical thinking toolkit for anyone who works with data but never plans to code.
4.18
480
📊 Data Literacy📈 Business Analytics🧠 Statistical Thinking🔍 Data Skepticism🤖 Machine Learning Basics
Becoming a Data Head Summary
Becoming a Data Head 92%
The critical thinking toolkit for anyone who works with data but never plans to code.
by Alex J. Gutman 2021
4.18
480 ratings
📊 Data Literacy📈 Business Analytics🧠 Statistical Thinking🔍 Data Skepticism🤖 Machine Learning Basics
Modern Software Engineering
by David Farley • 2021
Software is not a craft; it's a science. The discipline that turns teams into learning machines.
4.16
1k+
🔬 Scientific Engineering🔄 Continuous Delivery🔁 Feedback Loops🧱 Modularity🧪 Testability
Modern Software Engineering Summary
Modern Software Engineering 92%
Software is not a craft; it's a science. The discipline that turns teams into learning machines.
by David Farley 2021
4.16
1k+ ratings
🔬 Scientific Engineering🔄 Continuous Delivery🔁 Feedback Loops🧱 Modularity🧪 Testability
Practices of an Agile Developer
by Venkat Subramaniam • 2006
Clever code breaks teams; clear code lasts. Daily disciplines that turn a coder into a pro.
3.88
1k+
🔄 Agile Software Development🛠️ Software Craftsmanship📝 Clean Code🧪 Test-Driven Development🔁 Continuous Integration
Practices of an Agile Developer Summary
Practices of an Agile Developer 92%
Clever code breaks teams; clear code lasts. Daily disciplines that turn a coder into a pro.
by Venkat Subramaniam 2006
3.88
1k+ ratings
🔄 Agile Software Development🛠️ Software Craftsmanship📝 Clean Code🧪 Test-Driven Development🔁 Continuous Integration
How Computers Really Work
by Matthew Justice • 2020
From transistor to web: the computing stack explained layer by layer, no prerequisites required.
4.35
160
🏗️ Computer Architecture⚡ Digital Electronics🧱 Abstraction Layers💻 Computing Fundamentals🔧 How Things Work
How Computers Really Work Summary
How Computers Really Work 92%
From transistor to web: the computing stack explained layer by layer, no prerequisites required.
by Matthew Justice 2020
4.35
160 ratings
🏗️ Computer Architecture⚡ Digital Electronics🧱 Abstraction Layers💻 Computing Fundamentals🔧 How Things Work
Data Smart
by John W. Foreman • 2013
Real machine learning inside Excel: cluster customers, forecast demand, optimize decisions. No code.
4.12
1k+
📊 Spreadsheet Modeling📈 Business Analytics🤖 Machine Learning For Managers🧮 Quantitative Decision Making🔮 Forecasting Methods
Data Smart Summary
Data Smart 91%
Real machine learning inside Excel: cluster customers, forecast demand, optimize decisions. No code.
by John W. Foreman 2013
4.12
1k+ ratings
📊 Spreadsheet Modeling📈 Business Analytics🤖 Machine Learning For Managers🧮 Quantitative Decision Making🔮 Forecasting Methods
Coders at Work
by Peter Seibel • 2009
Fifteen master programmers on how they think, debug, and design: the craft in their own words.
3.95
5k+
🧑‍💻 Software Engineering🎙️ Developer Interviews🔨 Craft Of Programming🗣️ Polyglot Programming🕵️ Hacker Culture
Coders at Work Summary
Coders at Work 91%
Fifteen master programmers on how they think, debug, and design: the craft in their own words.
by Peter Seibel 2009
3.95
5k+ ratings
🧑‍💻 Software Engineering🎙️ Developer Interviews🔨 Craft Of Programming🗣️ Polyglot Programming🕵️ Hacker Culture
Why Data Science Projects Fail
by Douglas Gray • 2024
Eighty percent of AI projects fail. The models work fine; the people, data, and expectations don't.
5.00
19
📊 Data Science Management🤖 Ai Implementation⚙️ Mlops🧹 Data Quality🔧 Data Engineering
Why Data Science Projects Fail Summary
Why Data Science Projects Fail 91%
Eighty percent of AI projects fail. The models work fine; the people, data, and expectations don't.
by Douglas Gray 2024
5.00
19 ratings
📊 Data Science Management🤖 Ai Implementation⚙️ Mlops🧹 Data Quality🔧 Data Engineering
Apprenticeship Patterns
by Dave Hoover • 2009
Promotion pulls coders away from code. The patterns for staying in the craft while still advancing.
4.10
963
🛠️ Software Craftsmanship🧑‍🏭 Apprenticeship Model🏋️ Deliberate Practice🗺️ Pattern Languages🔄 Feedback Loops
Apprenticeship Patterns Summary
Apprenticeship Patterns 91%
Promotion pulls coders away from code. The patterns for staying in the craft while still advancing.
by Dave Hoover 2009
4.10
963 ratings
🛠️ Software Craftsmanship🧑‍🏭 Apprenticeship Model🏋️ Deliberate Practice🗺️ Pattern Languages🔄 Feedback Loops
Storytelling with Data
by Cole Nussbaumer Knaflic • 2015
A repeatable process for turning messy spreadsheets into clear charts that drive action.
4.38
8k+
🖥️ Data Visualization💼 Business Communication📊 Data Storytelling👁️ Visual Perception🎤 Presentation Skills
Storytelling with Data Summary
Storytelling with Data 91%
A repeatable process for turning messy spreadsheets into clear charts that drive action.
by Cole Nussbaumer Knaflic 2015
4.38
8k+ ratings
🖥️ Data Visualization💼 Business Communication📊 Data Storytelling👁️ Visual Perception🎤 Presentation Skills
The Pragmatic Programmer
by Andy Hunt • 1999
The habits and instincts that turn junior coders into trusted pros: a programmer's survival guide.
4.33
24k+
🧱 Software Craftsmanship🧹 Code Quality📚 Continuous Learning🧪 Test Driven Development📐 Software Design
The Pragmatic Programmer Summary
The Pragmatic Programmer 91%
The habits and instincts that turn junior coders into trusted pros: a programmer's survival guide.
by Andy Hunt 1999
4.33
24k+ ratings
🧱 Software Craftsmanship🧹 Code Quality📚 Continuous Learning🧪 Test Driven Development📐 Software Design
The Programmer's Brain
by Felienne Hermans • 2021
Syntax slips overnight; complex code confuses you. The cognitive fix no programming class taught.
3.85
416
📖 Code Comprehension🧠 Cognitive Load🧩 Mental Models⏳ Spaced Repetition🐛 Debugging Strategies
The Programmer's Brain Summary
The Programmer's Brain 91%
Syntax slips overnight; complex code confuses you. The cognitive fix no programming class taught.
by Felienne Hermans 2021
3.85
416 ratings
📖 Code Comprehension🧠 Cognitive Load🧩 Mental Models⏳ Spaced Repetition🐛 Debugging Strategies
The Nature of Code
by Daniel Shiffman • 2012
Code that breathes: how to build simulations that move, think, and evolve on your screen.
4.57
502
🎨 Creative Coding🖼️ Generative Art🟩 Cellular Automata❄️ Fractal Geometry🧬 Genetic Algorithms
The Nature of Code Summary
The Nature of Code 91%
Code that breathes: how to build simulations that move, think, and evolve on your screen.
by Daniel Shiffman 2012
4.57
502 ratings
🎨 Creative Coding🖼️ Generative Art🟩 Cellular Automata❄️ Fractal Geometry🧬 Genetic Algorithms
Intelligent IoT Projects in 7 Days
by Agus Kurniawan • 2017
Build a firefighting robot, a talking speaker, and five more connected devices in one week.
🖥️ Internet Of Things🔌 Embedded Systems📚 Project-Based Learning⚡ Microcontrollers📡 Sensor Networks
Intelligent IoT Projects in 7 Days Summary
Intelligent IoT Projects in 7 Days 91%
Build a firefighting robot, a talking speaker, and five more connected devices in one week.
by Agus Kurniawan 2017
🖥️ Internet Of Things🔌 Embedded Systems📚 Project-Based Learning⚡ Microcontrollers📡 Sensor Networks
Madly, Deeply
by Alan Rickman • 2022
Systems must evolve, not freeze: automated guardrails, small batches, and teams shaped for change.
3.58
17k+
🛠️ Software Architecture🚀 Continuous Delivery🧩 Microservices🔄 Agile Methodology👥 Team Organization
Madly, Deeply Summary
Madly, Deeply 91%
Systems must evolve, not freeze: automated guardrails, small batches, and teams shaped for change.
by Alan Rickman 2022
3.58
17k+ ratings
🛠️ Software Architecture🚀 Continuous Delivery🧩 Microservices🔄 Agile Methodology👥 Team Organization
The Road to React
by Robin Wieruch • 2017
Learn React the way it's actually written: hooks-first, project-driven, and tested from day one.
4.21
564
🖥️ Frontend Development📦 Javascript Ecosystem🧱 Component-Based Architecture🔄 State Management🧪 Software Testing
The Road to React Summary
The Road to React 91%
Learn React the way it's actually written: hooks-first, project-driven, and tested from day one.
by Robin Wieruch 2017
4.21
564 ratings
🖥️ Frontend Development📦 Javascript Ecosystem🧱 Component-Based Architecture🔄 State Management🧪 Software Testing
The Model Thinker
by Scott E. Page • 2018
Big data without many models is just noise. The case for thinking through multiple frameworks.
3.92
955
🧠 Mental Models🔄 Systems Thinking🌀 Complexity Science📊 Quantitative Reasoning🕸️ Network Theory
The Model Thinker Summary
The Model Thinker 91%
Big data without many models is just noise. The case for thinking through multiple frameworks.
by Scott E. Page 2018
3.92
955 ratings
🧠 Mental Models🔄 Systems Thinking🌀 Complexity Science📊 Quantitative Reasoning🕸️ Network Theory
Understanding and Using C Pointers
by Richard Reese • 2013
Pointers are C's sharpest tool. This is how to stop cutting yourself.
4.15
183
🖥️ C Programming👉 Pointers In C🧠 Memory Management⚙️ System Programming🗄️ Data Structures In C
Understanding and Using C Pointers Summary
Understanding and Using C Pointers 91%
Pointers are C's sharpest tool. This is how to stop cutting yourself.
by Richard Reese 2013
4.15
183 ratings
🖥️ C Programming👉 Pointers In C🧠 Memory Management⚙️ System Programming🗄️ Data Structures In C
How to Speak Machine
by John Maeda • 2019
Loops, scale, and unfinished products: what computers know that designers must learn.
3.69
521
🖥️ Computational Thinking📱 Digital Design🔄 Iterative Development⚖️ Algorithmic Bias📊 Data-Driven Design
How to Speak Machine Summary
How to Speak Machine 91%
Loops, scale, and unfinished products: what computers know that designers must learn.
by John Maeda 2019
3.69
521 ratings
🖥️ Computational Thinking📱 Digital Design🔄 Iterative Development⚖️ Algorithmic Bias📊 Data-Driven Design
Deep Learning
by John D. Kelleher • 2019
Deep learning isn't clever math. It's simple neurons, wired at scale, learning from their mistakes.
3.89
473
🔬 Deep Learning🧠 Neural Networks🤖 Machine Learning📘 Ai Fundamentals🔗 Connectionism
Deep Learning Summary
Deep Learning 91%
Deep learning isn't clever math. It's simple neurons, wired at scale, learning from their mistakes.
by John D. Kelleher 2019
3.89
473 ratings
🔬 Deep Learning🧠 Neural Networks🤖 Machine Learning📘 Ai Fundamentals🔗 Connectionism
The Math of Life and Death
by Kit Yates • 2019
Key mathematical ideas govern medicine, law, and media, and your intuition gets each one wrong.
3.90
2k+
🧮 Popular Mathematics📐 Applied Mathematics📊 Statistical Literacy🧠 Cognitive Biases⚠️ Risk Literacy
The Math of Life and Death Summary
The Math of Life and Death 91%
Key mathematical ideas govern medicine, law, and media, and your intuition gets each one wrong.
by Kit Yates 2019
3.90
2k+ ratings
🧮 Popular Mathematics📐 Applied Mathematics📊 Statistical Literacy🧠 Cognitive Biases⚠️ Risk Literacy
Cryptography
by Keith M. Martin • 2020
Your digital life depends on secret math. Who should be able to break it?
3.96
174
🔒 Digital Security🔐 Encryption👁️ Digital Privacy📐 Applied Mathematics📡 Surveillance
Cryptography Summary
Cryptography 91%
Your digital life depends on secret math. Who should be able to break it?
by Keith M. Martin 2020
3.96
174 ratings
🔒 Digital Security🔐 Encryption👁️ Digital Privacy📐 Applied Mathematics📡 Surveillance
Working Effectively with Legacy Code
by Michael C. Feathers • 2004
Every change is surgery in the dark. The proven, repeatable path to taming an untested codebase.
4.14
5k+
🧓 Legacy Code🔧 Software Maintenance🧪 Unit Testing🔄 Code Refactoring🎛️ Testability
Working Effectively with Legacy Code Summary
Working Effectively with Legacy Code 91%
Every change is surgery in the dark. The proven, repeatable path to taming an untested codebase.
by Michael C. Feathers 2004
4.14
5k+ ratings
🧓 Legacy Code🔧 Software Maintenance🧪 Unit Testing🔄 Code Refactoring🎛️ Testability
Designing Machine Learning Systems
by Chip Huyen • 2022
Accuracy is not enough. An iterative playbook for machine learning systems that survive production.
4.45
1k+
⚙️ Machine Learning Engineering🔧 Mlops🔄 Iterative Design📋 Reproducible Ml🤝 Ensemble Learning
Designing Machine Learning Systems Summary
Designing Machine Learning Systems 91%
Accuracy is not enough. An iterative playbook for machine learning systems that survive production.
by Chip Huyen 2022
4.45
1k+ ratings
⚙️ Machine Learning Engineering🔧 Mlops🔄 Iterative Design📋 Reproducible Ml🤝 Ensemble Learning
Building Secure and Reliable Systems
by Heather Adkins • 2020
Build systems that survive attacks and accidents. Google's framework for reliable, secure software.
3.89
199
🛡️ Software Security🔧 Site Reliability🔄 Devops Practices🔒 Secure Coding🧪 Testing Strategies
Building Secure and Reliable Systems Summary
Building Secure and Reliable Systems 91%
Build systems that survive attacks and accidents. Google's framework for reliable, secure software.
by Heather Adkins 2020
3.89
199 ratings
🛡️ Software Security🔧 Site Reliability🔄 Devops Practices🔒 Secure Coding🧪 Testing Strategies
Pluses and Minuses
by Stefan Buijsman • 2018
Three mathematical discoveries run your digital life; understanding them is simpler than you think.
3.41
290
🧮 Applied Mathematics📜 History Of Mathematics🔢 Mathematical Literacy🖥️ Mathematical Modeling🕸️ Network Theory
Pluses and Minuses Summary
Pluses and Minuses 91%
Three mathematical discoveries run your digital life; understanding them is simpler than you think.
by Stefan Buijsman 2018
3.41
290 ratings
🧮 Applied Mathematics📜 History Of Mathematics🔢 Mathematical Literacy🖥️ Mathematical Modeling🕸️ Network Theory
The Master Algorithm
by Pedro Domingos • 2015
Machine learning's rival schools share a hidden core. Finding it could unlock general intelligence.
3.73
6k+
🤖 Machine Learning📚 Popular Science🧠 Superintelligence📊 Big Data⚖️ Ai Ethics
The Master Algorithm Summary
The Master Algorithm 91%
Machine learning's rival schools share a hidden core. Finding it could unlock general intelligence.
by Pedro Domingos 2015
3.73
6k+ ratings
🤖 Machine Learning📚 Popular Science🧠 Superintelligence📊 Big Data⚖️ Ai Ethics
Refactoring to Patterns
by Joshua Kerievsky • 2004
How to transform tangled code into textbook patterns one small, safe step at a time.
4.05
1k+
🧱 Software Architecture✨ Code Quality🏗️ Object Oriented Design🌱 Evolutionary Design🧩 Design Patterns
Refactoring to Patterns Summary
Refactoring to Patterns 91%
How to transform tangled code into textbook patterns one small, safe step at a time.
by Joshua Kerievsky 2004
4.05
1k+ ratings
🧱 Software Architecture✨ Code Quality🏗️ Object Oriented Design🌱 Evolutionary Design🧩 Design Patterns
Software Engineering at Google
by Titus Winters • 2020
Google's testing playbook: 80/20, test behaviors not methods, write tests that never rot.
4.20
2k+
🧪 Software Testing🏗️ Engineering Culture🤖 Automated Testing🎯 Behavior-Driven Testing📋 Code Quality
Software Engineering at Google Summary
Software Engineering at Google 91%
Google's testing playbook: 80/20, test behaviors not methods, write tests that never rot.
by Titus Winters 2020
4.20
2k+ ratings
🧪 Software Testing🏗️ Engineering Culture🤖 Automated Testing🎯 Behavior-Driven Testing📋 Code Quality
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