Interesting links

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Historical

• Timesharing explained by MIT (Part 1 of 2)
• Timesharing explained by MIT (Part 2 of 2)

Operating Systems

• Linux Kernel Insides
• The container is a lie!
• Container creation with namespaces and bash
• Is Parallel Programming Hard, And, If So,What Can You Do About It?

Hardware

• A high-level overview of the bridge between hardware and software
• The Thirty Million Line Problem

Graphics

• How to build a renderer (How OpenGL works)
• The OpenGL Book
• The Book of Shaders

Law

• The myth of the rule of law

Science

• How to Read a Paper. The Three-Pass Approach

Compilers

• The Bits Between the Bits: How We Get to main() - Matt Godbolt
• What every systems programmer should know about concurrency

Computer Science

• Bob Jenkin's primer on hashing
• Crash-only software
• Jonathan Blow - Preventing the Collapse of Civilization
• Gerard Holzmann - Mars Code
• MIT OCW - Software Engineering Concepts
• Buridan's Principle

Software Engineering

• No Silver Bullet - Essence and Accident in Computer Science, Frederick Brooks
• Code as Crime Scene
• A Practical Tutorial on Modified Condition/Decision Coverage
• A Practical Approach to Modified Condition/Decision Coverage
• Tun/Tap interface tutorial
• A Domain-Specific Language Based Architecture Modeling Approach for Safety Critical Automotive Software Systems

Rust

• A Gentle Introduction To Rust

Machine Learning

• OpenDetection
• mlpack
• Lifelong Machine Learning Systems: Beyond Learning Algorithms

Neural Networks

• The GoogLeNet paper
• The vowpal wabbit network
• Image analogies convolutional network
• Training a Spiking Neural Network to Control a 4-DoF Robotic Arm based on Spike Timing-Dependent Plasticity
• Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis
• Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artwork
• Image analogies showcase
• Short LeNet intro
• Mastering the game of Go with deep neural networks and tree search
• Dropout: A Simple Way to Prevent Neural Networks from Overfitting
• Deep Learning Flappy Bird
• Demystifying Deep Reinforcement Learning
• Warren S.'s awesome neural nets FAQ - part 1, Introduction
• Warren S.'s awesome neural nets FAQ - part 2, Learning
• Warren S.'s awesome neural nets FAQ - part 3, Generalization
• Squeeze-and-Excitation Networks
• Transforming Auto-encoders - G. E. Hinton, A. Krizhevsky & S. D. Wang
• FlowNet: Learning Optical Flow with Convolutional Networks
• FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

Datasets

• MRPT Mobile Robotics dataset

Robotics

• Mobile Robotics Programming Toolkit
• Intuition on Kalman Filters
• FastSLAM: An Efficient Solution to the Simultaneous Localization And Mapping Problem with Unknown Data Association
• FastSLAM 2.0: An Improved Particle Filtering Algorithm for Simultaneous Localization and Mapping that Provably Converges
• Rapidly-Exploring Random Trees
• Adaptive Road Following using Self-Supervised Learning and Reverse Optical Flow

Space

• Basics of Space Flight - Rocket & Space Technology

Other

• Handball Training and Moves
• A Systematic Approach to Safety Case Management
• Redprint: Integrating API Specific "Instant Example" and "Instant Documentation" Display Interface in IDEs
• Civilization: Institutions, Knowledge and the Future - Samo Burja
• Why Google needed a graph serving system
• A New Colormap for MATLAB – Part 1 – Introduction
• A New Colormap for MATLAB – Part 2 – Troubles with Rainbows
• A New Colormap for MATLAB – Part 3 – Some Reactions
• Real System Failures