📦 Data Compression

Technical and conceptual explorations of how vast quantities of information are distilled into smaller forms, from ZIP files to streaming video, balancing fidelity against efficiency.

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 📡 Digital Communications ⚡ Electrical Engineering

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 📡 Digital Communications ⚡ Electrical Engineering

Fundamentals of Digital Image Processing

by Anil K. Jain • 1988

From pixel to picture: the math that samples, restores, compresses, and reconstructs digital images.

3.98

145

🖼️ Image Processing 📡 Signal Processing 〰️ Fourier Analysis 🏥 Medical Imaging 🔧 Image Restoration

Fundamentals of Digital Image Processing Summary

Fundamentals of Digital Image Processing 88%

From pixel to picture: the math that samples, restores, compresses, and reconstructs digital images.

by Anil K. Jain 1988

3.98

145 ratings

🖼️ Image Processing 📡 Signal Processing 〰️ Fourier Analysis 🏥 Medical Imaging 🔧 Image Restoration

Hadoop

by Tom White • 2009

How to turn cheap servers into a petabyte-scale data platform, from HDFS to real-time streaming.

3.93

1k+

📊 Big Data 🖧 Distributed Systems 🐘 Hadoop Ecosystem ⚙️ Data Engineering 🔗 Data Pipelines

Hadoop 88%

How to turn cheap servers into a petabyte-scale data platform, from HDFS to real-time streaming.

by Tom White 2009

3.93

1k+ ratings

📊 Big Data 🖧 Distributed Systems 🐘 Hadoop Ecosystem ⚙️ Data Engineering 🔗 Data Pipelines

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 88%

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 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 87%

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

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 87%

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

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 87%

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

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 87%

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

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 87%

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

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 87%

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

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 87%

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

Data Strategy

by Bernard Marr • 2017

Profit from the data firehose: pick the right data, build a company that acts on it.

3.77

418

📊 Data Strategy 📈 Business Intelligence 💾 Big Data 🧮 Analytics 🔒 Data Governance

Data Strategy 87%

Profit from the data firehose: pick the right data, build a company that acts on it.

by Bernard Marr 2017

3.77

418 ratings

📊 Data Strategy 📈 Business Intelligence 💾 Big Data 🧮 Analytics 🔒 Data Governance

Data Structures and Algorithms Made Easy in Java

by Narasimha Karumanchi • 2011

Data structures and algorithms, taught problem by problem in Java. Built for the interview.

4.17

471

🧱 Data Structures 🔧 Algorithm Design 💼 Coding Interviews ☕ Java Programming 📚 Cs Fundamentals

Data Structures and Algorithms Made Easy in Java Summary

Data Structures and Algorithms Made Easy in Java 87%

Data structures and algorithms, taught problem by problem in Java. Built for the interview.

by Narasimha Karumanchi 2011

4.17

471 ratings

🧱 Data Structures 🔧 Algorithm Design 💼 Coding Interviews ☕ Java Programming 📚 Cs Fundamentals

Google Hacks

by Rael Dornfest • 2003

Hidden syntax, tools, and 800 million Usenet messages: how to find anything with Google.

3.68

301

🔍 Internet Research 🔎 Search Techniques 💻 Hacker Culture 📢 Online Advertising ⚡ Power User Tips

Google Hacks 87%

Hidden syntax, tools, and 800 million Usenet messages: how to find anything with Google.

by Rael Dornfest 2003

3.68

301 ratings

🔍 Internet Research 🔎 Search Techniques 💻 Hacker Culture 📢 Online Advertising ⚡ Power User Tips

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 87%

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

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 87%

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

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 87%

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

Learning Python Data Visualization

by Chad Adams • 2014

Turn spreadsheets and web data into SVG charts with Python, no design background required.

3.00

📊 Data Visualization 🐍 Python Programming 📈 Chart Creation 🎨 Svg Graphics 🕸️ Web Scraping

Learning Python Data Visualization Summary

Learning Python Data Visualization 87%

Turn spreadsheets and web data into SVG charts with Python, no design background required.

by Chad Adams 2014

3.00

5 ratings

📊 Data Visualization 🐍 Python Programming 📈 Chart Creation 🎨 Svg Graphics 🕸️ Web Scraping

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 87%

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

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 87%

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

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 87%

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

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 87%

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

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 87%

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

Graph Databases

by Ian Robinson • 2013

Relational databases fail on connected data. Graph databases traverse deep links in milliseconds.

3.64

437

🕸️ Graph Databases 🗄️ Nosql Databases 📐 Graph Theory 🔗 Network Analysis 🏗️ Data Architecture

Graph Databases 87%

Relational databases fail on connected data. Graph databases traverse deep links in milliseconds.

by Ian Robinson 2013

3.64

437 ratings

🕸️ Graph Databases 🗄️ Nosql Databases 📐 Graph Theory 🔗 Network Analysis 🏗️ Data Architecture

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 87%

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

Big Data

by Viktor Mayer-Schönberger • 2013

The era of sampling, clean data, and causal certainty is over. What replaces it is stranger.

3.69

9k+

💰 Data As Asset 📈 Predictive Analytics 🧹 Imperfect Data 🌐 Quantified World 🔗 Correlation Analysis

Big Data 87%

The era of sampling, clean data, and causal certainty is over. What replaces it is stranger.

by Viktor Mayer-Schönberger 2013

3.69

9k+ ratings

💰 Data As Asset 📈 Predictive Analytics 🧹 Imperfect Data 🌐 Quantified World 🔗 Correlation Analysis

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 87%

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

Fundamentals of Data Engineering

by Joe Reis • 2022

Data scientists spend 80% of their time cleaning data. The systems blueprint that frees them.

4.16

945

🛠️ Data Engineering 🏗️ Data Architecture 🔗 Data Pipelines 📊 Data Modeling ☁️ Cloud Data Systems

Fundamentals of Data Engineering Summary

Fundamentals of Data Engineering 87%

Data scientists spend 80% of their time cleaning data. The systems blueprint that frees them.

by Joe Reis 2022

4.16

945 ratings

🛠️ Data Engineering 🏗️ Data Architecture 🔗 Data Pipelines 📊 Data Modeling ☁️ Cloud Data Systems

Python for Informatics

by Charles Severance • 2002

Learn Python by probing data: scrape the web, query databases, and make the file system obey.

3.99

619

🐍 Python Programming 📘 Introductory Programming ℹ️ Informatics 🔄 Data Manipulation 🕸️ Web Scraping

Python for Informatics 87%

Learn Python by probing data: scrape the web, query databases, and make the file system obey.

by Charles Severance 2002

3.99

619 ratings

🐍 Python Programming 📘 Introductory Programming ℹ️ Informatics 🔄 Data Manipulation 🕸️ Web Scraping

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 87%

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

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 87%

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

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 87%

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

Context

by Cory Doctorow • 2011

3.66

372

🕸️ Internet Freedom 📜 Copyright Reform 🔐 Digital Rights 🏛️ Platform Politics 📚 Digital Publishing

Context 87%

by Cory Doctorow 2011

3.66

372 ratings

🕸️ Internet Freedom 📜 Copyright Reform 🔐 Digital Rights 🏛️ Platform Politics 📚 Digital Publishing

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 87%

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

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 87%

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 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 87%

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

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 86%

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

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 86%

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

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 86%

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

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 86%

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

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 86%

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

The Art of Debugging with GDB, DDD and Eclipse

by Norman Matloff • 2007

Your program crashes because it hides a secret. GDB, DDD, and Eclipse reveal it.

3.91

106

🐞 Debugging Techniques ⚡ Systems Programming 🧠 Memory Management 🐧 Linux Development ⚙️ Concurrent Programming

The Art of Debugging with GDB, DDD and Eclipse Summary

The Art of Debugging with GDB, DDD and Eclipse 86%

Your program crashes because it hides a secret. GDB, DDD, and Eclipse reveal it.

by Norman Matloff 2007

3.91

106 ratings

🐞 Debugging Techniques ⚡ Systems Programming 🧠 Memory Management 🐧 Linux Development ⚙️ Concurrent Programming

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 86%

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

Practical Packet Analysis

by Chris Sanders • 2007

Slow network, DNS failures, intruders: Wireshark finds the cause when dashboards cannot.

4.10

431

📦 Packet Analysis 🔧 Network Troubleshooting 🦈 Wireshark 🔎 Network Forensics 🌐 TCP/IP

Practical Packet Analysis 86%

Slow network, DNS failures, intruders: Wireshark finds the cause when dashboards cannot.

by Chris Sanders 2007

4.10

431 ratings

📦 Packet Analysis 🔧 Network Troubleshooting 🦈 Wireshark 🔎 Network Forensics 🌐 TCP/IP

Linux Service Management Made Easy with systemd

by Donald A. Tevault • 2022

Parallel startup, unified configs, binary logs: the systemd skills every Linux admin now needs.

3.81

🐧 Linux Administration 🖥️ System Administration 🗄️ Server Management 🔧 It Infrastructure 💻 Command Line

Linux Service Management Made Easy with systemd Summary

Linux Service Management Made Easy with systemd 86%

Parallel startup, unified configs, binary logs: the systemd skills every Linux admin now needs.

by Donald A. Tevault 2022

3.81

21 ratings

🐧 Linux Administration 🖥️ System Administration 🗄️ Server Management 🔧 It Infrastructure 💻 Command Line

Python Data Science

by Christopher Wilkinson • 2019

Python taught for data science: syntax, data structures, and the libraries that unlock the field.

2.50

🐍 Python Programming 📊 Data Science 📐 Programming Fundamentals 🔧 Data Analysis Tools 🌐 Python Ecosystem

Python Data Science 86%

Python taught for data science: syntax, data structures, and the libraries that unlock the field.

by Christopher Wilkinson 2019

2.50

2 ratings

🐍 Python Programming 📊 Data Science 📐 Programming Fundamentals 🔧 Data Analysis Tools 🌐 Python Ecosystem

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 86%

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

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 86%

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

Cybersecurity for Small Networks

by Seth Enoka • 2022

Turn free tools into a layered defense that stops attackers before they reach your devices.

4.08

🔒 Network Security 🏠 Homelab And Self-Hosting 🛠️ Open Source Tools 🧅 Defense In Depth 🚨 Intrusion Detection

Cybersecurity for Small Networks Summary

Cybersecurity for Small Networks 86%

Turn free tools into a layered defense that stops attackers before they reach your devices.

by Seth Enoka 2022

4.08

52 ratings

🔒 Network Security 🏠 Homelab And Self-Hosting 🛠️ Open Source Tools 🧅 Defense In Depth 🚨 Intrusion Detection

Designing Data-Intensive Applications

by Martin Kleppmann • 2015

Networks fail, clocks drift, consensus is elusive. The big ideas behind systems that work anyway.

4.70

11k+

🖥️ Distributed Systems 🗄️ Database Design 🤝 Consensus Algorithms 🛡️ Fault Tolerance 📊 Consistency Models

Designing Data-Intensive Applications Summary

Designing Data-Intensive Applications 86%

Networks fail, clocks drift, consensus is elusive. The big ideas behind systems that work anyway.

by Martin Kleppmann 2015

4.70

11k+ ratings

🖥️ Distributed Systems 🗄️ Database Design 🤝 Consensus Algorithms 🛡️ Fault Tolerance 📊 Consistency Models

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