🎯 Optimization Methods

Technical and applied guides to mathematical optimization — algorithms, models, and computational techniques for finding the best solutions in engineering, logistics, and beyond.

Thinking Better

by Marcus du Sautoy • 2021

Mathematical shortcuts that save time, solve problems, and show you what everyone else overlooks.

3.59

618

🧮 Mathematical Thinking 🧠 Mental Shortcuts 🔍 Pattern Recognition ⚙️ Optimization 👁️ Visual Thinking

Thinking Better 90%

Mathematical shortcuts that save time, solve problems, and show you what everyone else overlooks.

by Marcus du Sautoy 2021

3.59

618 ratings

🧮 Mathematical Thinking 🧠 Mental Shortcuts 🔍 Pattern Recognition ⚙️ Optimization 👁️ Visual Thinking

Algorithm Design

by Jon Kleinberg • 2005

Design algorithms that run fast; recognize the problems that never will; and learn the workarounds.

4.17

664

🧮 Algorithm Design ⏱️ Computational Complexity 🕸️ Graph Theory 🧩 Dynamic Programming 🚫 Np Completeness

Algorithm Design 90%

Design algorithms that run fast; recognize the problems that never will; and learn the workarounds.

by Jon Kleinberg 2005

4.17

664 ratings

🧮 Algorithm Design ⏱️ Computational Complexity 🕸️ Graph Theory 🧩 Dynamic Programming 🚫 Np Completeness

Neural Networks, Fuzzy Logic And Genetic Algorithms

by S. Rajasekaran • 2004

Soft computing's three pillars each have blind spots. This is how they fill each other's gaps.

4.21

151

🖥️ Soft Computing 🧠 Neural Networks 🌫️ Fuzzy Logic 🧬 Genetic Algorithms 🤖 Machine Learning

Neural Networks, Fuzzy Logic And Genetic Algorithms Summary

Neural Networks, Fuzzy Logic And Genetic Algorithms 90%

Soft computing's three pillars each have blind spots. This is how they fill each other's gaps.

by S. Rajasekaran 2004

4.21

151 ratings

🖥️ Soft Computing 🧠 Neural Networks 🌫️ Fuzzy Logic 🧬 Genetic Algorithms 🤖 Machine Learning

Mastering Regular Expressions

by Jeffrey E.F. Friedl • 1997

Understand the engine behind your regex: why some patterns crawl, and how to make them run.

4.16

2k+

🧩 Regular Expressions 📝 Text Processing 🔍 Pattern Matching ⚡ Code Optimization 🤖 Automata Theory

Mastering Regular Expressions 89%

Understand the engine behind your regex: why some patterns crawl, and how to make them run.

by Jeffrey E.F. Friedl 1997

4.16

2k+ ratings

🧩 Regular Expressions 📝 Text Processing 🔍 Pattern Matching ⚡ Code Optimization 🤖 Automata Theory

AI for Data Science

by Zacharias Voulgaris • 2018

The real AI toolkit goes beyond deep learning: optimization, fuzzy logic, ensembles.

4.55

📊 Data Science 🧠 Deep Learning ⚙️ Optimization Algorithms 🤝 Ensemble Methods 📈 Big Data Analytics

AI for Data Science 89%

The real AI toolkit goes beyond deep learning: optimization, fuzzy logic, ensembles.

by Zacharias Voulgaris 2018

4.55

20 ratings

📊 Data Science 🧠 Deep Learning ⚙️ Optimization Algorithms 🤝 Ensemble Methods 📈 Big Data Analytics

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 89%

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

The Great Mental Models Volume 3

by Rhiannon Beaubien • 2021

The world runs on feedback loops and bottlenecks you never see. The models that expose them.

4.25

832

🧠 Mental Models 🔄 Systems Thinking 🛡️ Risk Management ⚡ Optimization 🎲 Randomness

The Great Mental Models Volume 3 Summary

The Great Mental Models Volume 3 89%

The world runs on feedback loops and bottlenecks you never see. The models that expose them.

by Rhiannon Beaubien 2021

4.25

832 ratings

🧠 Mental Models 🔄 Systems Thinking 🛡️ Risk Management ⚡ Optimization 🎲 Randomness

High Performance Web Sites

by Steve Souders • 2007

The browser, not the backend, eats your load time. The engineering rules that win it back.

4.15

688

🚀 Web Performance ⚙️ Performance Engineering 📡 HTTP Optimization 💾 Caching Strategies 🌐 Content Delivery Networks

High Performance Web Sites 89%

The browser, not the backend, eats your load time. The engineering rules that win it back.

by Steve Souders 2007

4.15

688 ratings

🚀 Web Performance ⚙️ Performance Engineering 📡 HTTP Optimization 💾 Caching Strategies 🌐 Content Delivery Networks

Writing High-Performance .NET Code

by Ben Watson • 2014

Stop guessing why .NET drags. Measure, master the GC, and fix the real bottlenecks.

4.30

291

💻 .Net Development ⚡ Performance Tuning 💾 Memory Management 🔄 Asynchronous Programming 📊 Code Profiling

Writing High-Performance .NET Code Summary

Writing High-Performance .NET Code 88%

Stop guessing why .NET drags. Measure, master the GC, and fix the real bottlenecks.

by Ben Watson 2014

4.30

291 ratings

💻 .Net Development ⚡ Performance Tuning 💾 Memory Management 🔄 Asynchronous Programming 📊 Code Profiling

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 88%

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

The 80/20 Principle

by Richard Koch • 1997

Most of what you work on barely matters. The playbook for finding the fraction that does.

3.98

31k+

🤑 Profit Optimization 📊 Power Laws 🎯 Selective Focus ⏰ Time Leverage 🔍 Complexity Reduction

The 80/20 Principle 88%

Most of what you work on barely matters. The playbook for finding the fraction that does.

by Richard Koch 1997

3.98

31k+ ratings

🤑 Profit Optimization 📊 Power Laws 🎯 Selective Focus ⏰ Time Leverage 🔍 Complexity Reduction

Algorithms to Live By

by Brian Christian • 2016

When to settle, when to quit, when to trust chance: computer science already found the answers.

4.12

35k+

🧠 Algorithmic Thinking 🔬 Decision Science 📊 Bayesian Reasoning 🧩 Heuristics 💭 Overthinking

Algorithms to Live By 88%

When to settle, when to quit, when to trust chance: computer science already found the answers.

by Brian Christian 2016

4.12

35k+ ratings

🧠 Algorithmic Thinking 🔬 Decision Science 📊 Bayesian Reasoning 🧩 Heuristics 💭 Overthinking

My Good Grief

by Cindyanne Kershaw • 2006

Seen enough options? There is a mathematically optimal moment to stop looking and commit.

4.50

💻 Applied Computer Science 🔬 Science-Based Self-Help 🤔 Rational Decision Making 📊 Bayesian Reasoning 🎲 Game Theory Applications

My Good Grief 88%

Seen enough options? There is a mathematically optimal moment to stop looking and commit.

by Cindyanne Kershaw 2006

4.50

2 ratings

💻 Applied Computer Science 🔬 Science-Based Self-Help 🤔 Rational Decision Making 📊 Bayesian Reasoning 🎲 Game Theory Applications

The Principles of Product Development Flow

by Donald G. Reinertsen • 2009

Product development waste hides in its invisible queues. The fix is not process, it is economics.

4.19

3k+

🏗️ Product Development 📊 Queueing Theory 💰 Economic Decision Making 🌊 Flow Optimization 📦 Small Batch Production

The Principles of Product Development Flow Summary

The Principles of Product Development Flow 88%

Product development waste hides in its invisible queues. The fix is not process, it is economics.

by Donald G. Reinertsen 2009

4.19

3k+ ratings

🏗️ Product Development 📊 Queueing Theory 💰 Economic Decision Making 🌊 Flow Optimization 📦 Small Batch Production

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 88%

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

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 88%

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

Fundamental Methods of Mathematical Economics

by Alpha C. Chiang • 1974

Economics explained in equations: a rigorous toolkit from statics to dynamic systems.

4.02

541

🧮 Mathematical Economics 📊 Economic Modeling ⚖️ Equilibrium Analysis ↔️ Comparative Statics ⏳ Dynamic Economics

Fundamental Methods of Mathematical Economics Summary

Fundamental Methods of Mathematical Economics 88%

Economics explained in equations: a rigorous toolkit from statics to dynamic systems.

by Alpha C. Chiang 1974

4.02

541 ratings

🧮 Mathematical Economics 📊 Economic Modeling ⚖️ Equilibrium Analysis ↔️ Comparative Statics ⏳ Dynamic Economics

Shape

by Jordan Ellenberg • 2021

Geometry is not about triangles. It is the hidden structure of pandemics, search, and democracy.

3.73

2k+

Shape 88%

Geometry is not about triangles. It is the hidden structure of pandemics, search, and democracy.

by Jordan Ellenberg 2021

3.73

2k+ ratings

Automate Your Busywork

by Aytekin Tank • 2023

Most of your workday runs on repeat. The no-code playbook for automating it away.

3.29

391

🤖 Workflow Automation 🔁 Continuous Improvement ⚙️ Personal Systems 📐 Lean Methodology 🔗 Systems Thinking

Automate Your Busywork 88%

Most of your workday runs on repeat. The no-code playbook for automating it away.

by Aytekin Tank 2023

3.29

391 ratings

🤖 Workflow Automation 🔁 Continuous Improvement ⚙️ Personal Systems 📐 Lean Methodology 🔗 Systems Thinking

Why Machines Learn

by Anil Ananthaswamy • 2024

The perceptron flopped but the math stayed: the linear algebra and calculus that built the AI age.

4.38

1k+

📜 History Of Ai 🧬 Deep Learning 🧠 Neural Network Theory 📐 Linear Algebra 🔢 Mathematical Foundations

Why Machines Learn 88%

The perceptron flopped but the math stayed: the linear algebra and calculus that built the AI age.

by Anil Ananthaswamy 2024

4.38

1k+ ratings

📜 History Of Ai 🧬 Deep Learning 🧠 Neural Network Theory 📐 Linear Algebra 🔢 Mathematical Foundations

Essentials of Supply Chain Management

by Michael H. Hugos • 2002

Five levers control every supply chain. Tuning their balance beats optimizing any single one.

3.78

280

🏭 Supply Chain Management ⚙️ Operations Management 🚚 Logistics Planning 📦 Inventory Optimization 📊 Performance Metrics

Essentials of Supply Chain Management Summary

Essentials of Supply Chain Management 88%

Five levers control every supply chain. Tuning their balance beats optimizing any single one.

by Michael H. Hugos 2002

3.78

280 ratings

🏭 Supply Chain Management ⚙️ Operations Management 🚚 Logistics Planning 📦 Inventory Optimization 📊 Performance Metrics

Algorithms of the Intelligent Web

by Haralambos Marmanis • 2009

Search, recommend, cluster, classify: the algorithms that make web applications intelligent.

3.62

130

🤖 Machine Learning 🌐 Web Applications 🎯 Recommendation Systems 📄 Text Mining ⛏️ Data Mining

Algorithms of the Intelligent Web Summary

Algorithms of the Intelligent Web 88%

Search, recommend, cluster, classify: the algorithms that make web applications intelligent.

by Haralambos Marmanis 2009

3.62

130 ratings

🤖 Machine Learning 🌐 Web Applications 🎯 Recommendation Systems 📄 Text Mining ⛏️ Data Mining

The Algorithm Design Manual

by Steven S. Skiena • 1997

The first step is modeling, not coding. A practical manual and its 75-problem catalog show how.

4.34

3k+

🧩 Algorithm Design 🗃️ Data Structures 🕸️ Graph Algorithms 🔢 Dynamic Programming 🛠️ Practical Algorithms

The Algorithm Design Manual 88%

The first step is modeling, not coding. A practical manual and its 75-problem catalog show how.

by Steven S. Skiena 1997

4.34

3k+ ratings

🧩 Algorithm Design 🗃️ Data Structures 🕸️ Graph Algorithms 🔢 Dynamic Programming 🛠️ Practical Algorithms

Guesstimation

by Lawrence Weinstein • 2008

How to answer impossible questions with a napkin, a pen, and a few simple guesses.

3.75

432

📝 Back-Of-The-Envelope Math ⚛️ Everyday Physics 🔢 Quantitative Reasoning 🧩 Problem-Solving Heuristics 🤔 Physical Intuition

Guesstimation 88%

How to answer impossible questions with a napkin, a pen, and a few simple guesses.

by Lawrence Weinstein 2008

3.75

432 ratings

📝 Back-Of-The-Envelope Math ⚛️ Everyday Physics 🔢 Quantitative Reasoning 🧩 Problem-Solving Heuristics 🤔 Physical Intuition

Introduction to Algorithms

by Thomas H. Cormen • 1989

Sorting a billion records can take days or seconds, depending on the algorithm, not the processor.

4.35

9k+

📘 Algorithms 🗂️ Data Structures 📊 Algorithm Analysis ✂️ Divide And Conquer 🎲 Randomized Algorithms

Introduction to Algorithms 88%

Sorting a billion records can take days or seconds, depending on the algorithm, not the processor.

by Thomas H. Cormen 1989

4.35

9k+ ratings

📘 Algorithms 🗂️ Data Structures 📊 Algorithm Analysis ✂️ Divide And Conquer 🎲 Randomized Algorithms

The Art of SEO

by Eric Enge • 2009

Master the link graph: why relevance, trust, and timing matter more than the vote count alone.

4.10

923

🖥️ Search Engine Optimization 📈 Digital Marketing 🔗 Link Building 🔍 Search Algorithms 🤍 White Hat Seo

The Art of SEO 88%

Master the link graph: why relevance, trust, and timing matter more than the vote count alone.

by Eric Enge 2009

4.10

923 ratings

🖥️ Search Engine Optimization 📈 Digital Marketing 🔗 Link Building 🔍 Search Algorithms 🤍 White Hat Seo

The Little Book of Deep Learning

by 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 Summary

The Little Book of Deep Learning 88%

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

by François Fleuret 2023

4.32

151 ratings

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

Cracking the Coding Interview

by Gayle Laakmann McDowell • 2020

189 interview problems that teach you to think out loud, because code follows from thinking.

4.33

476

🧑‍💻 Coding Interviews 🧠 Algorithm Problems 🗂️ Data Structures 🧑‍🏫 New Engineers ⏱️ Big O Notation

Cracking the Coding Interview 88%

189 interview problems that teach you to think out loud, because code follows from thinking.

by Gayle Laakmann McDowell 2020

4.33

476 ratings

🧑‍💻 Coding Interviews 🧠 Algorithm Problems 🗂️ Data Structures 🧑‍🏫 New Engineers ⏱️ Big O Notation

Robin Hood Math

by Noah Giansiracusa • 2025

Algorithms price your insurance, rank your resume, curate your reality. The math that fights back.

3.91

185

🧮 Algorithmic Literacy 🛡️ Digital Self-Defense 📐 Applied Mathematics 📊 Bayesian Reasoning 📉 Everyday Statistics

Robin Hood Math 88%

Algorithms price your insurance, rank your resume, curate your reality. The math that fights back.

by Noah Giansiracusa 2025

3.91

185 ratings

🧮 Algorithmic Literacy 🛡️ Digital Self-Defense 📐 Applied Mathematics 📊 Bayesian Reasoning 📉 Everyday Statistics

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 88%

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

Programming Interviews Exposed

by John Mongan • 2000

The data structures coding interviews reuse, and the method for talking through your work.

3.96

1k+

🖥️ Coding Interviews 💻 CS Fundamentals 📊 Data Structures 🔢 Algorithm Design ⏱️ Big-O Analysis

Programming Interviews Exposed 88%

The data structures coding interviews reuse, and the method for talking through your work.

by John Mongan 2000

3.96

1k+ ratings

🖥️ Coding Interviews 💻 CS Fundamentals 📊 Data Structures 🔢 Algorithm Design ⏱️ Big-O Analysis

Introduction to Computation and Programming Using Python

by John V. Guttag • 2013

A computer calculates and remembers; everything beyond that is what you build with code.

4.22

500

🧑‍💻 Introductory Programming 🧠 Computational Thinking 🐍 Python For Beginners 📐 Algorithm Design 🗃️ Data Structures

Introduction to Computation and Programming Using Python Summary

Introduction to Computation and Programming Using Python 88%

A computer calculates and remembers; everything beyond that is what you build with code.

by John V. Guttag 2013

4.22

500 ratings

🧑‍💻 Introductory Programming 🧠 Computational Thinking 🐍 Python For Beginners 📐 Algorithm Design 🗃️ Data Structures

Python for Data Analysis

by Oscar Scratch • 2019

Python data analysis, taught through questions: NumPy, Pandas, and the bridge to machine learning.

3.50

🧮 Scientific Computing 🔄 Data Manipulation 📊 Data Visualization 🐍 Introductory Programming 📈 Beginner Data Science

Python for Data Analysis 88%

Python data analysis, taught through questions: NumPy, Pandas, and the bridge to machine learning.

by Oscar Scratch 2019

3.50

2 ratings

🧮 Scientific Computing 🔄 Data Manipulation 📊 Data Visualization 🐍 Introductory Programming 📈 Beginner Data Science

TRIZ For Dummies

by Lilly Haines-Gadd • 2016

Turn impossible trade-offs into breakthroughs. A patent-proven method for systematic innovation.

4.07

🧠 Systematic Innovation 📦 Product Development 💡 Creative Problem Solving ⚖️ Design Trade-Offs 🔭 Technology Forecasting

TRIZ For Dummies 88%

Turn impossible trade-offs into breakthroughs. A patent-proven method for systematic innovation.

by Lilly Haines-Gadd 2016

4.07

54 ratings

🧠 Systematic Innovation 📦 Product Development 💡 Creative Problem Solving ⚖️ Design Trade-Offs 🔭 Technology Forecasting

How to Get to the Top of Google Search

by Richard Conway • 2019

Outrank your competitors on Google. A practical guide to search visibility for business owners.

4.38

🔍 Search Engine Optimization 🔑 Keyword Research 🔗 Link Building 📄 Content Strategy 📍 Local Search

How to Get to the Top of Google Search Summary

How to Get to the Top of Google Search 88%

Outrank your competitors on Google. A practical guide to search visibility for business owners.

by Richard Conway 2019

4.38

13 ratings

🔍 Search Engine Optimization 🔑 Keyword Research 🔗 Link Building 📄 Content Strategy 📍 Local Search

The Art of Computer Programming, Volume 1

by Donald Ervin Knuth • 1973

Algorithms are not just code: they are mathematical objects. To understand one, you must prove it.

4.38

2k+

🧮 Algorithm Design 🗂️ Data Structures 📈 Algorithm Analysis 📐 Mathematical Analysis 🔧 Low-Level Computing

The Art of Computer Programming, Volume 1 Summary

The Art of Computer Programming, Volume 1 88%

Algorithms are not just code: they are mathematical objects. To understand one, you must prove it.

by Donald Ervin Knuth 1973

4.38

2k+ ratings

🧮 Algorithm Design 🗂️ Data Structures 📈 Algorithm Analysis 📐 Mathematical Analysis 🔧 Low-Level Computing

Credit Scoring and Its Applications

by Lyn C. Thomas • 1987

How the algorithms that decide who gets a loan actually work, and how to build them.

3.62

💳 Credit Risk 🏦 Consumer Lending 📊 Statistical Modeling 🔮 Predictive Analytics ⚙️ Operational Research

Credit Scoring and Its Applications Summary

Credit Scoring and Its Applications 88%

How the algorithms that decide who gets a loan actually work, and how to build them.

by Lyn C. Thomas 1987

3.62

13 ratings

💳 Credit Risk 🏦 Consumer Lending 📊 Statistical Modeling 🔮 Predictive Analytics ⚙️ Operational Research

Nonlinear Dynamics and Chaos

by Steven H. Strogatz • 1994

How simple rules produce unpredictable motion, and the pictures that reveal the hidden order.

4.38

2k+

🌀 Nonlinear Dynamics 🕸️ Complex Systems 📊 Mathematical Modeling 🦋 Deterministic Chaos 🔗 Synchronization

Nonlinear Dynamics and Chaos 88%

How simple rules produce unpredictable motion, and the pictures that reveal the hidden order.

by Steven H. Strogatz 1994

4.38

2k+ ratings

🌀 Nonlinear Dynamics 🕸️ Complex Systems 📊 Mathematical Modeling 🦋 Deterministic Chaos 🔗 Synchronization

The Logical Thinking Process

by H. William Dettmer • 2007

A systematic method to identify and break the one bottleneck holding your entire organization back.

4.38

160

🧠 Systems Thinking 🔗 Constraint Management 🔁 Continuous Improvement 🔍 Root Cause Analysis 🧩 Logical Frameworks

The Logical Thinking Process 88%

A systematic method to identify and break the one bottleneck holding your entire organization back.

by H. William Dettmer 2007

4.38

160 ratings

🧠 Systems Thinking 🔗 Constraint Management 🔁 Continuous Improvement 🔍 Root Cause Analysis 🧩 Logical Frameworks

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 88%

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

The Art of SQL

by Stephane Faroult • 2006

SQL performance lives in the gap between relational theory and disk reality.

3.98

170

🗄️ Database Design 🚀 Query Optimization 🏭 Data Warehousing 📐 Relational Theory 🔍 Indexing Strategies

The Art of SQL 88%

SQL performance lives in the gap between relational theory and disk reality.

by Stephane Faroult 2006

3.98

170 ratings

🗄️ Database Design 🚀 Query Optimization 🏭 Data Warehousing 📐 Relational Theory 🔍 Indexing Strategies

How to Solve It

by George Pólya • 1944

Most problems are not solved by attacking them harder but by approaching them sideways.

4.12

5k+

🔍 Problem-Solving Heuristics 🧮 Mathematical Thinking 🧠 Heuristic Reasoning 📚 Math Pedagogy 🔄 Analogical Reasoning

How to Solve It 88%

Most problems are not solved by attacking them harder but by approaching them sideways.

by George Pólya 1944

4.12

5k+ ratings

🔍 Problem-Solving Heuristics 🧮 Mathematical Thinking 🧠 Heuristic Reasoning 📚 Math Pedagogy 🔄 Analogical Reasoning

The Ethical Algorithm

by Michael Kearns • 2019

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

4.10

671

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

The Ethical Algorithm 88%

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

by Michael Kearns 2019

4.10

671 ratings

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

Computer Science Distilled

by Wladston Ferreira Filho • 2017

The missing CS toolkit for self-taught coders: how to think in algorithms, not just syntax.

4.07

1k+

🧠 Computational Thinking 🧮 Algorithm Design 🗂️ Data Structures 📊 Complexity Analysis 🎲 Probability Theory

Computer Science Distilled 88%

The missing CS toolkit for self-taught coders: how to think in algorithms, not just syntax.

by Wladston Ferreira Filho 2017

4.07

1k+ ratings

🧠 Computational Thinking 🧮 Algorithm Design 🗂️ Data Structures 📊 Complexity Analysis 🎲 Probability Theory

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 88%

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

Street-Fighting Mathematics

by Sanjoy Mahajan • 2010

A toolkit for rough-and-ready problem solving: estimate with units, symmetry, and clever shortcuts.

3.74

236

✏️ Back-Of-The-Envelope 📏 Dimensional Analysis 💡 Heuristic Reasoning 🔬 Physical Intuition 🧮 Mathematical Modeling

Street-Fighting Mathematics 88%

A toolkit for rough-and-ready problem solving: estimate with units, symmetry, and clever shortcuts.

by Sanjoy Mahajan 2010

3.74

236 ratings

✏️ Back-Of-The-Envelope 📏 Dimensional Analysis 💡 Heuristic Reasoning 🔬 Physical Intuition 🧮 Mathematical Modeling

Game Programming Patterns

by Robert Nystrom • 2011

The programming patterns that make game code resilient to change, and the ones that don't.

4.49

2k+

🎮 Game Programming 🧩 Design Patterns 🏗️ Software Architecture ⚡ Performance Optimization 🔗 Decoupling

Game Programming Patterns 88%

The programming patterns that make game code resilient to change, and the ones that don't.

by Robert Nystrom 2011

4.49

2k+ ratings

🎮 Game Programming 🧩 Design Patterns 🏗️ Software Architecture ⚡ Performance Optimization 🔗 Decoupling

Superagency

by Reid Hoffman • 2025

AI multiplies human agency. That power will concentrate or spread. The choice is ours.

3.33

1k+

🏛️ Ai Policy 🌅 Tech Optimism ⚖️ Ai Ethics 🔮 Future Of Work 📊 Data Governance

Superagency 88%

AI multiplies human agency. That power will concentrate or spread. The choice is ours.

by Reid Hoffman 2025

3.33

1k+ ratings

🏛️ Ai Policy 🌅 Tech Optimism ⚖️ Ai Ethics 🔮 Future Of Work 📊 Data Governance

Introduction to Linear Algebra

by Gilbert Strang • 1993

Linear algebra organized around a matrix's core spaces: from elimination straight to the SVD.

4.24

703

📐 Applied Linear Algebra 🧩 Matrix Factorizations ↔️ Vector Spaces 💻 Computational Mathematics 🤖 Machine Learning Math

Introduction to Linear Algebra 88%

Linear algebra organized around a matrix's core spaces: from elimination straight to the SVD.

by Gilbert Strang 1993

4.24

703 ratings

📐 Applied Linear Algebra 🧩 Matrix Factorizations ↔️ Vector Spaces 💻 Computational Mathematics 🤖 Machine Learning Math

Everyday Chaos

by David Weinberger • 2019

A medical AI diagnoses illness but can't explain how. The age of demanding explanations is over.

3.78

202

🔬 Complexity Science 🔄 Systems Thinking 🤖 Machine Learning 💻 Digital Strategy 🔓 Open Platforms

Everyday Chaos 88%

A medical AI diagnoses illness but can't explain how. The age of demanding explanations is over.

by David Weinberger 2019

3.78

202 ratings

🔬 Complexity Science 🔄 Systems Thinking 🤖 Machine Learning 💻 Digital Strategy 🔓 Open Platforms

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