🔢 Numerical Computing

The algorithms and techniques that allow computers to solve complex mathematical problems approximately, powering everything from weather models to financial simulations.

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 91%

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

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 90%

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

PYTHON FOR DATA ANALYSIS

by Ryshith Doyle • 2019

The systematic NumPy and Pandas walkthrough: import, clean, combine, and analyze data in Python.

3.67

🐍 Python Programming 📊 Data Analysis 🧹 Data Wrangling 🧱 Data Structures 🚀 Beginner Programmers

PYTHON FOR DATA ANALYSIS 90%

The systematic NumPy and Pandas walkthrough: import, clean, combine, and analyze data in Python.

by Ryshith Doyle 2019

3.67

6 ratings

🐍 Python Programming 📊 Data Analysis 🧹 Data Wrangling 🧱 Data Structures 🚀 Beginner Programmers

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 90%

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

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 90%

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

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 90%

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

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 90%

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

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 90%

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

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 90%

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

Python for Data Analysis

by Wes McKinney • 2011

The pandas creator teaches the full Python data pipeline: messy files in, statistical models out.

4.17

2k+

🧹 Data Wrangling 🔬 Scientific Computing 📊 Data Visualization ⏳ Time Series Analysis 📈 Statistical Modeling

Python for Data Analysis 90%

The pandas creator teaches the full Python data pipeline: messy files in, statistical models out.

by Wes McKinney 2011

4.17

2k+ ratings

🧹 Data Wrangling 🔬 Scientific Computing 📊 Data Visualization ⏳ Time Series Analysis 📈 Statistical Modeling

Python Programming

by John Zelle • 2003

A Python-first CS textbook that teaches what computation can do, not just how to code.

4.02

483

📘 Introductory Programming 🐍 Python Programming 🧮 Algorithm Fundamentals 🏗️ Object-Oriented Design 🔄 Software Development

Python Programming 90%

A Python-first CS textbook that teaches what computation can do, not just how to code.

by John Zelle 2003

4.02

483 ratings

📘 Introductory Programming 🐍 Python Programming 🧮 Algorithm Fundamentals 🏗️ Object-Oriented Design 🔄 Software Development

Python Data Science Handbook

by Jake VanderPlas • 2016

Four libraries, one workflow: the Python path from raw data to validated predictions.

4.29

676

📊 Data Science 🤖 Machine Learning 🐍 Scientific Python 🧹 Data Preprocessing ⚙️ Feature Engineering

Python Data Science Handbook 89%

Four libraries, one workflow: the Python path from raw data to validated predictions.

by Jake VanderPlas 2016

4.29

676 ratings

📊 Data Science 🤖 Machine Learning 🐍 Scientific Python 🧹 Data Preprocessing ⚙️ Feature Engineering

Python for Finance

by Yves Hilpisch • 2012

Python's finance stack: vectorized data, Monte Carlo methods, deploying models from Excel to web.

3.80

249

📊 Quantitative Finance 🔢 Financial Modeling 🎲 Monte Carlo Simulation 💻 Computational Finance 🐍 Python Ecosystem

Python for Finance 89%

Python's finance stack: vectorized data, Monte Carlo methods, deploying models from Excel to web.

by Yves Hilpisch 2012

3.80

249 ratings

📊 Quantitative Finance 🔢 Financial Modeling 🎲 Monte Carlo Simulation 💻 Computational Finance 🐍 Python Ecosystem

Practical Statistics for Data Scientists

by Peter Bruce • 2017

The statistical methods data scientists use daily, from boxplots to bootstrap, minus the proofs.

4.02

545

🛠️ Practical Data Science 📈 Applied Statistics 🔍 Exploratory Data Analysis 🎓 Statistical Inference 🔄 Resampling Methods

Practical Statistics for Data Scientists Summary

Practical Statistics for Data Scientists 89%

The statistical methods data scientists use daily, from boxplots to bootstrap, minus the proofs.

by Peter Bruce 2017

4.02

545 ratings

🛠️ Practical Data Science 📈 Applied Statistics 🔍 Exploratory Data Analysis 🎓 Statistical Inference 🔄 Resampling Methods

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 89%

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

Practical Statistics for Data Scientists

by 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 89%

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

by Peter Bruce 2020

4.21

261 ratings

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

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 89%

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

What's the Use?

by Ian Stewart • 2021

Kidney matches, secure websites, movie animation: the invisible math that built the modern world.

3.54

175

📐 Applied Mathematics 📊 Mathematical Modeling 🔍 Hidden Mathematics 🔢 Number Theory 🔗 Topology

What's the Use? 89%

Kidney matches, secure websites, movie animation: the invisible math that built the modern world.

by Ian Stewart 2021

3.54

175 ratings

📐 Applied Mathematics 📊 Mathematical Modeling 🔍 Hidden Mathematics 🔢 Number Theory 🔗 Topology

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+

The Math of Life and Death 89%

Key mathematical ideas govern medicine, law, and media, and your intuition gets each one wrong.

by Kit Yates 2019

3.90

2k+ ratings

Data Structures and Algorithms Made Easy

by Narasimha Karumanchi • 2011

Every algorithm problem has multiple solutions. Find the fastest one, step by step.

4.10

1k+

⏱️ Algorithm Analysis 🗃️ Data Structures ✍️ Algorithm Design 📊 Complexity Theory 💼 Coding Interviews

Data Structures and Algorithms Made Easy Summary

Data Structures and Algorithms Made Easy 89%

Every algorithm problem has multiple solutions. Find the fastest one, step by step.

by Narasimha Karumanchi 2011

4.10

1k+ ratings

⏱️ Algorithm Analysis 🗃️ Data Structures ✍️ Algorithm Design 📊 Complexity Theory 💼 Coding Interviews

The Little Book of Mathematical Principles, Theories & Things

by Robert Solomon • 2008

A compact tour through math's biggest ideas: zero, infinity, and the proof that broke mathematics.

3.97

438

🏛️ History Of Mathematics 📐 Math Primers 🧱 Mathematical Foundations 🔢 Number Theory 💻 History Of Computing

The Little Book of Mathematical Principles, Theories & Things Summary

The Little Book of Mathematical Principles, Theories & Things 89%

A compact tour through math's biggest ideas: zero, infinity, and the proof that broke mathematics.

by Robert Solomon 2008

3.97

438 ratings

🏛️ History Of Mathematics 📐 Math Primers 🧱 Mathematical Foundations 🔢 Number Theory 💻 History Of Computing

Learning OpenCV

by Gary Bradski • 2008

From smoothing to machine learning: the complete OpenCV toolkit for building computer vision apps.

4.01

171

🖥️ Computer Vision 🌄 Image Processing 📚 Open Source Libraries ⚙️ Algorithm Guides 📖 Code Reference

Learning OpenCV 89%

From smoothing to machine learning: the complete OpenCV toolkit for building computer vision apps.

by Gary Bradski 2008

4.01

171 ratings

🖥️ Computer Vision 🌄 Image Processing 📚 Open Source Libraries ⚙️ Algorithm Guides 📖 Code Reference

Data Science from Scratch

by Joel Grus • 2015

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

3.90

1k+

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

Data Science from Scratch 89%

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

by Joel Grus 2015

3.90

1k+ ratings

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

Information Theory, Coding and Crytography

by Ranjan Bose • 2002

Entropy sets the limit. Coding reaches it. Cryptography locks it. One textbook covers all three.

3.75

162

🧠 Information Theory 🔢 Coding Theory 🔐 Cryptography 📦 Data Compression 📡 Digital Communications

Information Theory, Coding and Crytography Summary

Information Theory, Coding and Crytography 89%

Entropy sets the limit. Coding reaches it. Cryptography locks it. One textbook covers all three.

by Ranjan Bose 2002

3.75

162 ratings

🧠 Information Theory 🔢 Coding Theory 🔐 Cryptography 📦 Data Compression 📡 Digital Communications

Data Structures and Algorithms

by Alfred V. Aho • 1983

Write code that scales: the classic mathematical toolkit for reasoning about speed before you run.

3.93

245

🧱 Data Structures ⏱️ Algorithm Analysis 🔨 Algorithm Design 💡 Language-Agnostic Programming 🔢 Sorting Algorithms

Data Structures and Algorithms 89%

Write code that scales: the classic mathematical toolkit for reasoning about speed before you run.

by Alfred V. Aho 1983

3.93

245 ratings

🧱 Data Structures ⏱️ Algorithm Analysis 🔨 Algorithm Design 💡 Language-Agnostic Programming 🔢 Sorting Algorithms

Structured Computer Organization

by Andrew S. Tanenbaum • 1976

From logic gates to assembly code: the layered architecture every computer hides in plain sight.

4.04

591

🏗️ Computer Architecture 🧅 Layered Abstraction 🔌 Digital Logic 🧩 Parallel Computing 🖥️ Operating Systems

Structured Computer Organization Summary

Structured Computer Organization 89%

From logic gates to assembly code: the layered architecture every computer hides in plain sight.

by Andrew S. Tanenbaum 1976

4.04

591 ratings

🏗️ Computer Architecture 🧅 Layered Abstraction 🔌 Digital Logic 🧩 Parallel Computing 🖥️ Operating Systems

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 89%

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

Python for Geeks

by Muhammad Asif • 2021

Machine learning from notebook to production: Python libraries, data prep, and deployment paths.

4.50

🐍 Python Programming ⚙️ Machine Learning Engineering 📊 Data Science 🚀 Production Deployment ☁️ Serverless Computing

Python for Geeks 89%

Machine learning from notebook to production: Python libraries, data prep, and deployment paths.

by Muhammad Asif 2021

4.50

8 ratings

🐍 Python Programming ⚙️ Machine Learning Engineering 📊 Data Science 🚀 Production Deployment ☁️ Serverless Computing

Grokking Algorithms An Illustrated Guide For Programmers and Other Curious People

by Aditya Y. Bhargava • 2015

Algorithms stripped of dense math: a hand-drawn guide to thinking in runtimes and data structures.

4.41

5k+

🔢 Algorithm Fundamentals 🧱 Data Structures 🔍 Sorting And Searching 🕸️ Graph Algorithms ✏️ Illustrated Guides

Grokking Algorithms An Illustrated Guide For Programmers and Other Curious People Summary

Grokking Algorithms An Illustrated Guide For Programmers and Other Curious People 89%

Algorithms stripped of dense math: a hand-drawn guide to thinking in runtimes and data structures.

by Aditya Y. Bhargava 2015

4.41

5k+ ratings

🔢 Algorithm Fundamentals 🧱 Data Structures 🔍 Sorting And Searching 🕸️ Graph Algorithms ✏️ Illustrated Guides

Shape

by Jordan Ellenberg • 2021

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

3.73

2k+

Shape 89%

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

by Jordan Ellenberg 2021

3.73

2k+ ratings

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 89%

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

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 89%

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 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 89%

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

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 89%

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

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

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 89%

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

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 89%

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

Think Stats

by Allen B. Downey • 2011

Statistics taught through code: why simulation and real data beat memorization every time.

3.64

469

💻 Computational Statistics 🔍 Exploratory Data Analysis 🐍 Python Data Analysis 📊 Statistical Modeling 🎲 Hypothesis Testing

Think Stats 89%

Statistics taught through code: why simulation and real data beat memorization every time.

by Allen B. Downey 2011

3.64

469 ratings

💻 Computational Statistics 🔍 Exploratory Data Analysis 🐍 Python Data Analysis 📊 Statistical Modeling 🎲 Hypothesis Testing

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

Speed Mathematics

by Bill Handley • 2003

Calculate faster than a calculator using only a pencil, a circle, and simple subtraction.

3.98

146

🧮 Mental Arithmetic ✂️ Calculation Shortcuts ⚡ Rapid Calculation 🧠 Memory Systems 🛒 Everyday Mathematics

Speed Mathematics 89%

Calculate faster than a calculator using only a pencil, a circle, and simple subtraction.

by Bill Handley 2003

3.98

146 ratings

🧮 Mental Arithmetic ✂️ Calculation Shortcuts ⚡ Rapid Calculation 🧠 Memory Systems 🛒 Everyday Mathematics

Automate This

by Christopher Steiner • 2012

Algorithms took Wall Street. Now they compose music, allocate kidneys, and profile personalities.

3.82

4k+

📈 Algorithmic Trading 🤖 Automation And Society 💻 Computational Thinking 🏛️ Wall Street History 🔮 Future Of Work

Automate This 89%

Algorithms took Wall Street. Now they compose music, allocate kidneys, and profile personalities.

by Christopher Steiner 2012

3.82

4k+ ratings

📈 Algorithmic Trading 🤖 Automation And Society 💻 Computational Thinking 🏛️ Wall Street History 🔮 Future Of Work

Arithmetic

by Paul Lockhart • 2017

Arithmetic is a craft, not a grind. The elegant patterns hiding in every counting system.

3.92

236

🧠 Mathematical Thinking 📜 History Of Math 🔢 Number Representation 🧮 Calculating Devices ✨ Patterns In Numbers

Arithmetic 89%

Arithmetic is a craft, not a grind. The elegant patterns hiding in every counting system.

by Paul Lockhart 2017

3.92

236 ratings

🧠 Mathematical Thinking 📜 History Of Math 🔢 Number Representation 🧮 Calculating Devices ✨ Patterns In Numbers

The Design of the UNIX Operating System

by Maurice J. Bach • 1986

What actually happens between the shell prompt and the hardware: the Unix kernel explained.

4.25

605

🖥️ Operating Systems ⚙️ Kernel Design 🔧 Systems Programming 📜 Unix Philosophy 📁 File Systems

The Design of the UNIX Operating System Summary

The Design of the UNIX Operating System 89%

What actually happens between the shell prompt and the hardware: the Unix kernel explained.

by Maurice J. Bach 1986

4.25

605 ratings

🖥️ Operating Systems ⚙️ Kernel Design 🔧 Systems Programming 📜 Unix Philosophy 📁 File Systems

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 89%

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

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 89%

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

Data Structures and Algorithms in Java

by Michael T. Goodrich • 1998

Data structures and their runtime analysis: how to write Java code that is efficient and dependable.

3.86

302

🧱 Data Structures ⚙️ Algorithms 🏗️ Algorithm Design 📈 Algorithm Analysis 🧩 Software Design

Data Structures and Algorithms in Java Summary

Data Structures and Algorithms in Java 89%

Data structures and their runtime analysis: how to write Java code that is efficient and dependable.

by Michael T. Goodrich 1998

3.86

302 ratings

🧱 Data Structures ⚙️ Algorithms 🏗️ Algorithm Design 📈 Algorithm Analysis 🧩 Software Design

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 89%

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

Algorithms + Data Structures = Programs

by Niklaus Wirth • 1975

Programs are just data structures shaped by algorithms. Master both, and the rest follows.

4.24

207

🔧 Software Engineering 🧮 Data Structures And Algorithms 📐 Structured Programming 🧩 Modular Design 🐛 Debugging Practices

Algorithms + Data Structures = Programs Summary

Algorithms + Data Structures = Programs 89%

Programs are just data structures shaped by algorithms. Master both, and the rest follows.

by Niklaus Wirth 1975

4.24

207 ratings

🔧 Software Engineering 🧮 Data Structures And Algorithms 📐 Structured Programming 🧩 Modular Design 🐛 Debugging Practices

Seven Concurrency Models in Seven Weeks

by Paul Butcher • 2014

Threads unravel programs. Seven concurrency models that don't, from actors and CSP to GPU parallel.

3.82

349

🧩 Concurrency Patterns ⚡ Parallel Programming 🎭 Actor Model λ Functional Concurrency 🎮 GPGPU Computing

Seven Concurrency Models in Seven Weeks Summary

Seven Concurrency Models in Seven Weeks 89%

Threads unravel programs. Seven concurrency models that don't, from actors and CSP to GPU parallel.

by Paul Butcher 2014

3.82

349 ratings

🧩 Concurrency Patterns ⚡ Parallel Programming 🎭 Actor Model λ Functional Concurrency 🎮 GPGPU Computing

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 89%

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

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