Luigi's Bookshelf

I am addicted to science and technology. Fortunately, there are many authors that kindly have made their textbooks available online for free.

Last update: June 23rd, 2025.

Subject Index

Physics
Chemistry
Geology
Mathematics
Computer Science
Finance and Economics
Entrepreneurship, Project Management and Marketing
Biology
- Neuroscience
Medicine

Physics

Feynman et al. - The Feynman Lectures on Physics

Chemistry

Gray - Chemical Bonds: An Introduction to Atomic and Molecular Structure
Gubler - Electrochemistry: Fundamentals, Cells & Applications - Lecture Notes 2023

Geology

Earle - Physical Geology, 2nd Ed.
Lüthi, Walter, Werder - Physics of Glaciers
Greve - Dynamics of Ice Sheets and Glaciers
Ray et al. - Landslides: Investigations and Monitoring
Kresic - Hydrology 101 - Introduction to Groundwater Science and Engineering
Freeze, Cherry - Groundwater
Anderson - New Theory of the Earth

Mathematics

Foundations and Logic

Russell - The Principles of Mathematics
Jarvis et al. - Foundations of Applied Mathematics
Gallier et al. Logic and Computation (Topology, Algebra, etc.)
Magnus - forallX - An Introduction to Formal Logic
Abelson et al. - Turtle Geometry: The Computer as a Medium for Exploring Mathematics
Smith - Beginning Mathematical Logic: A Study Guide
Smith - An Introduction to Formal Logic, 2nd Ed.
Hammack - Book of Proof, 3rd Ed.

Algebra

Ström et al. - Immersive Linear Algebra
Thomas - Computational Linear Algebra for Coders
Cherney et al. - Linear Algebra
Treil - Linear Algebra Done Wrong
Boyd et al. - Introduction to Applied Linear Algebra - Vectors, Matrices, and Least Squares
Ash - Abstract Algebra: The Basic Graduate Year
O’Donnell - Analysis of Boolean Functions
Axler - Linear Algebra Done Right, 4th Ed.
Margalit, Rabinoff, Williams - Interactive Linear Algebra

Calculus

Keisler - Elementary Calculus: An Infinitesimal Approach
Axler - Measure, Integration & Real Analysis
Dawkins - Paul’s Online Math Notes
Heinbockel - Introduction to Tensor Calculus and Continuum Mechanics
Tao - An Introduction to Measure Theory
Grady, Polimeni - Discrete Calculus: Applied Analysis on Graphs for Computational Science
Acquistapace - Appunti di Analisi 1 e 2 e Analisi Funzionale (in Italian)
Tricomi - Funzioni Analitiche (in Italian)
Jones - Computational Complex Analysis Särkkä - Applied Stochastic Differential Equations

Numerical Methods

Solomon - Numerical Algorithms
Linge et al. - Programming for Computations - A Gentle Introduction to Numerical Simulations with Python
Moler - Numerical Computing with MATLAB
Wick - Numerical Methods for Partial Differential Equations
Hennig, Osborne, Kersting - Probabilistic Numerics: Computation as Machine Learning
Brugnano - Modelli Numerici per la Simulazione
Linge, Langtangen - Programming for Computations - A Gentle Introduction to Numerical Simulations with Python or MATLAB/Octave
Langtangen, Logg - Solving PDEs in Python - The FEniCS Tutorial I
Langtangen, Linge - Finite Difference Computing with PDEs: A Modern Software Approach
Novak - Numerical Methods for Scientific Computing, 2nd Ed.
Spencer, Ware, Colton - Partial Differential Equations - Python Edition
Sundnes - Solving Ordinary Differential Equations in Python
Butler - Numerical Methods and Machine Learning for Differential Equations with Applications in Python

Geometry

Differential Geometry

Sussman et al. - Functional Differential Geometry
Crane - Discrete Differential Geometry: An Applied Introduction
Henderson - Differential Geometry: A Geometric Introduction

Topology

Ghrist - Elementary Applied Topology
Morris - Topology without tears
Hatcher - Algebraic Topology
Bradley et al. - Topology: A Categorical Approach
Dey et al. - Computational Topology for Data Analysis
Edelsbrunner et al. - Computational Topology: An Introduction
Cipolla, Giblin - Visual Motion of Curves and Surfaces

Computational Geometry

Goodman, O’Rourke, Tóth - Handbook of Discrete and Computational Geometry, 3rd Ed.

Probability and Statistics

Gelman et al. - Bayesian Data Analysis, 3rd Ed.
Gelman et al. - Regression and Other Stories
Gelman, Vehtari - Active Statistics
Lattimore et al. - Bandit Algorithms
Owen - Monte Carlo theory, methods and examples
Vershynin - High-Dimensional Probability and Applications in Data Science
Clyde et al. - An Introduction to Bayesian Thinking
Blitzstein - Introduction to Probability, 2nd Ed.
Kadane - Principles of Uncertainty, 2nd Ed.
Cranmer - Statistics and Data Science
Davidson-Pilon - Probabilistic Programming and Bayesian Methods for Hackers
Goodman et al. - Probabilistic Models of Cognition
Tanizaky - Computational Methods in Statistics and Econometrics
Johnson - Bayes Rules ! An Introduction to Bayesian Modeling with R
Martin et al. - Bayesian Modeling and Computation in Python
Wilf - generatingfunctionology, 2nd Ed.
Popov - Two-Dimensional Random Walk
Taleb - Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemoloy, and Applications
NIST/SEMATECH - e-Handbook of Statistical Methods
Durrett - Elementary Probability for Applications
Durrett - Probability: Theory and Examples, 5th Ed.
Neal - Probabilistic Inference using Markov Chain Monte Carlo Methods
Betancourt - A Conceptual Introduction to Hamiltonian Monte Carlo
Betancourt - Probabilistic Modeling with Stan
Stan Development Team - Stan User’s Guide
Marden - Multivariate Statistics: Old School
United Nations - Handbook on Management and Organization of National Statistical Systems
Gray - Probability, Random Processes, and Ergodic Properties
Baldini, Di Lalla, Razzano, Sgro’ - Introduzione all’analisi dei dati
Furrer - Introduction to Statistics: A Tour in 14 Weeks
Olive - Applied Robust Statistics
Honkela - Computational Statistics I
Ross - An Introduction to Bayesian Reasoning and Methods
van de Meent, Paige, Yang, Wood - An Introduction to Probabilistic Programming
Chacon, Duong - Multivariate Kernel Smoothing and Its Applications
Devroye - Non-Uniform Random Variate Generation

Stochastic Processes and Time Series

Subba Rao - A Course in Time Series Analysis
Hyndman et al. - Forecasting: Principles and Practice, 3rd Ed.
Gallager - Discrete Stochastic Processes
Durrett - Essential of Stochastic Processes
Särkkä, Solin - Applied Stochastic Differential Equations
Belzile - Time Series
Diebold - Forecasting in Economics, Business, Finance and Beyond
Diebold - Time-Series Econometrics: A Concise Course
Labbe - Kalman and Bayesian Filters in Python
Gumbel - Statistical Theory of Extreme Values and Some Practical Applications
Naess - Applied Extreme Value Statistics including the ACER method
Wiener - Extrapolation, Interpolation, and Smoothing of Stationary Time Series: With Engineering Applications
PennState University - STAT 510: Applied Time Series Analysis
Nair, Wierman, Zwart - The Fundamentals of Heavy Tails (Draft)

Causal Inference

Pearl - Causality
Pearl - Causal Inference in Statistics: A Primer
Hernan, Robins - Causal Inference: What If
Peters - Elements of Causal Inference
Sharma et al. - Causal Reasoning: Fundamentals and Machine Learning Applications
Facure Alves - Causal Inference for the Brave and True
Cunningham - Causal Inference: The Mixtape

Number Theory

Stein - Elementary Number Theory: Primes, Congruences, and Secrets
Shoup - A Computational Introduction to Number Theory and Algebra, 2nd Ed.

Optimization and Linear Programming

Dantzig - Linear Programming and Extensions
Vishnoi - Algorithms for Convex Optimization
Kochenderfer et al. - Algorithms for Optimization
Kochenderfer et al. - Algorithms for Decision Making
Kochenderfer et al. - Decision Making Under Uncertainty
Fourer et al. - AMPL: A Modeling Language for Mathematical Programming
Sallan et al. - Modeling and solving linear programming with R
Liberti - Mathematical Programming
Boyd et al. - Convex Optimization
Dattorro - Convex Optimization and Euclidean Distance Geometry
Villani - Optimal Transport, old and new
Peyre’ et al. - Computational Optimal Transport
Liberzon - Calculus of Variations and Optimal Control Theory
Anderson, Moore - Optimal Filtering
Lucchetti - Convexity and Well-Posed Problems
Hazan - Introduction to Online Convex Optimization
Lusby, Stidsen - Mathematical Programming with Julia
Kwon - Julia Programming for Operation Research. 2nd Ed.
Bubeck - Convex Optimization: Algorithms and Complexity
Absil, Mahony, Sepulchre - Optimization Algorithms on Matrix Manifolds
Bottou, Curtis, Nocedal - Optimization Methods for Large-Scale Machine Learning
Kall, Wallace - Stochastic Programming, 2nd Ed.
Sargent, Stachurski - Dynamic Programming
Williamson, Shmoys - The Design of Approximation Algorithms
Rawlings, Mayne, Diehl - Model Predictive Control: Theory, Computation, and Design, 2nd Ed.

Graph Theory

Barabasi - Network Science
Easley et al. - Network, Crowds, and Markets: Reasoning About a Highly Connected World
Lyons et al. - Probability on Trees and Networks
Guichard - An Introduction to Combinatorics and Graph Theory
Williamson - Network Flow Algorithms
Lovasz - Large networks and graph limits
van Steen - Graph Theory and Complex Networks
Frieze, Karonski - Introduction to Random Graphs
Diestel - Graph Theory, 5th Ed.
van der Hofstad - Random Graphs and Complex Networks, Volume I and II
Durrett - Dynamics on Graphs

Game Theory

Dresher - Games of Strategy - Theory and Applications
Shoham - Multiagent Systems
Karlin - Game Theory, Alive
Osborne - Introduction to Game Theory
Bonanno - Game Theory
Lucchetti - A Primer in Game Theory

Category Theory

Milewski - Category Theory for Programmers
Fong et al. - Seven Sketches in Compositionality: An Invitation to Applied Category Theory
Leinster - Basic Category Theory
Smith - Beginning Category Theory
Riehl - Category Theory in Context

Computer Science

Algorithms and Data Structures

Arora et al. - Computational Complexity: A Modern Approach
Bovet et al. - Introduction to the theory of complexity
Erickson - Algorithms
Di Pierro - Annotated Algorithms in Python
Flajolet et al. - Analytic Combinatorics
Keller, Trotter - Applied Combinatorics, 2017 Edition
Barack - Introduction to Theoretical Computer Science
Wigderson - Mathematics and Computation
Schloss et al. - Algorithm Archive
Needham et al. - Graph Algorithms
Arndt - Matters Computational: Ideas, Algorithms, Source Code
Sanders et al. - Sequential and Parallel Algorithms and Data Structures

Distributed Systems and High Performance Computing

van Steen et al. - Computer and Network Organization
van Steen, Tanenbaum - Distributed Systems, 4th Ed.
Burns - Designing Distributed Systems
Eijkhout - The Science of Computing, Vol.1
Eijkhout - Parallel Programming for Science and Engineering, Vol.2
Eijkhout - Introduction to Scientific Programming, Vol.3
Livermore Computing Center - Introduction to Parallel Computing Tutorial
Severance - High Performance Computing
Slotin - Algorithms for Modern Hardware
Reinders et al. - Data Parallel C++ - Mastering DPC++ for Programming of Heterogeneous System using C++ and SYCL
Arora, Barak - Computational Complexity: A Modern Approach

Computer Programming

Abelson et al. - Structure and Interpretation of Computer Programs, JavaScript Ed.
Cooper et al. - Engineering a Compiler
Stepanov et al. - Elements of Programming
Papert - Mindstorm - Children, Computers, and Powerful Ideas

C/C++

Banahan, Brady, Doran - The C Book

R

Wickham - Advanced R, 2nd Ed.
Phillips - YaRr! The Pirate’s Guide to R
Grolemund - Hand-on Programming with R

JavaScript

Haverbeke - Eloquent JavaScript, 3rd Ed.

Haskell

O’Sullivan et al. - Real World Haskell

Scala

Alexander - Scala Book

Java

Eck - Introduction to Programming Using Java, 8th Ed.

Python

Kong et al. - Python Programming and Numerical Methods
Sundnes - Introduction to Scientific Programming with Python
Hill - Learning Scientific Programming with Python
Sargent et al. - Python Programming for Economics and Finance
Sheppard - Introduction to Python for Econometrics, Statistics and Numerical Analysis, 4th Ed.

Rust

Klabnik, Nichols - The Rust Programming Language

Data Science

Hey et al. - The Fourth Paradigm: Data-Intensive Scientific Discovery
Wickham et al. - R for Data Science
VanderPlas - Python Data Science Handbook
Perlin - Analyzing Financial and Economic Data with R
Adhikari et al. - Computational and Inferential Thinking: The Foundations of Data Science, 2nd Ed.
Zacharski - A Programmer’s Guide to Data Mining
Janssens - Data Science at the Command Line, 2nd Ed.
Irizarry - Introduction to Data Science
Blum et al. - Foundation of Data Science
Ranjan Das - Data Science: Theories, Models, Algorithms and Analytics
Bouveyron et al. - Model-Based Clustering and Classification for Data Science
Rajamohan - Computational Statistics with PyMC3
McKinney - Python for Data Analysis, 3rd Ed.
Storopoli et al. - Julia Data Science
Wright et al. - High-Dimensional Data Analysis with Low-Dimensional Models: Principles, Computation, and Applications
Law et al. - Data Assimilation: A Mathematical Introduction
Lehman et al. - Mathematics for Computer Science
Peyre’ - Mathematical Foundations of Data Science
Peyre’ - An Introduction to Data Sciences
Baumer, Kaplan, Horton - Modern Data Science with R, 2nd Ed.
Brunton, Kutz - Data-Driven Science & Engineering
Spector, Norvig, Wiggins, Wing - Data Science in Context: Foundations, Challenges, Opportunities
Damji, Wenig, Das, Lee - Learning Spark, 2nd Ed.

Data Visualization

Healy - Data Visualization - A Practical Introduction
Wilke - Fundamentals of Data Visualization
Wickham - ggplot2: Elegant Graphics for Data Analysis, 2nd Ed.
Dougherty - Hands-On Data Visualization
Spencer - Data in Wonderland
Rougier - Scientific Visualization: Python + Matplotlib

Machine Learning

Daume’ III - A Course in Machine Learning
Simeone - A Brief Introduction to Machine Learning for Engineers
Google Machine Learning Crash Course
Parr et al. - The Mechanics of Machine Learning
Barber - Bayesian Reasoning and Machine Learning
Winn et al. - Model-Based Machine Learning
Kriesel - A Brief Introduction to Neural Networks
Molnar - Interpretable Machine Learning
Battiti et al. - The LION Way. Machine Learning plus Intelligent Optimization
Burkov - The Hundred Pages Machine Learning Book
Bobra - Machine Learning, Statistics, and Data Mining for Heliophysics
Bishop - Pattern Recognition and Machine Learning
Deisenroth et al. - Mathematics for Machine Learning
Rasmussen - Gaussian Processes for Machine Learning
Murphy - Probabilistic Machine Learning: An Introduction
Thakur - Approaching (Almost) Any Machine Learning Problem
Hardt et al. - Pattern, Predictions, and Actions
Treveil et al. - Introducing MLOp
Azencott - Introduction au Machine Learning
Mohri et al. - Foundations of Machine Learning, 2nd Ed.
Gerrish - How Smart Machines Think
James et al. - An Introduction to Statistical Learning, 2nd Ed.
Hastie et al. - The Elements of Statistical Learning, 2nd Ed.
Shalev-Shwartz et al. - Understanding Machine Learning: From Theory to Algorithms
Efron et al. - Computer Age Statistical Inference
Mitchell - Machine Learning
Wilber et al. - MLU-Explain: Visual explanation of core machine learning concepts
Shapire, Freund - Boosting: Foundations and Algorithms
Lindholm, Wahlström, Lindsten, Schön - Machine Learning: A First Course for Engineers and Scientists
Louppe - Understanding Random Forests: From Theory to Practice
Hutter, Kotthoff, Vanschoren, eds - Automated Machine Learning

Neural Networks, Deep Learning, and Reinforcement Learning

Goodfellow et al. - Deep Learning Book
Karpathy - CS231n Convolutional Neural Network for Visual Recognition
Rojas - Neural Networks - A Systematic Introduction
Hagan et al. - Neural Network Design, 2nd Ed.
Zhang et al. - Dive into Deep Learning
Hamilton - Graph Representation Learning
Howard et al. - Practical Deep Learning for Coders
Ma et al. - Deep Learning on Graphs
LeCun et al. - Deep Learning
Bronstein et al. Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Roberts et al. - The Principles of Deep Learning Theory
Sutton et al. - Reinforcement Learning, 2nd Ed.
Francois-Lavet et al. - An Introduction to Deep Reinforcement Learning
Nielsen - Neural Networks and Deep Learning
Bertsekas - Lessons from AlphaZero for Optimal, Model Predictive, and Adaptive Control
Kashani et al. - Deep Learning Inteviews: Hundreds of fully solved questions from a wide range of key topics in AI
Rao, Jelvis - Foundations of Reinforcement Learning with Applications in Finance
Nikolenko - Synthetic Data for Deep Learning
Akkus et al. - Multimodal Deep Learning
Kingma, Welling - An Introduction to variational Autoencoders
Wu, Cui, Pei, Zhao - Graph Neural Networks: Foundations, Frontiers, and Applications
Prince - Understanding Deep Learning
Fleuret - The Little Book of Deep Learning
Janzamin, Ge, Kossaifi, Anandkumar - Spectral Learning on Matrices and Tensors
Gal - Uncertainty in Deep Learning
Bishop, Bishop - Deep Learning: Foundations and Concepts
Scardapane - Alice’s Adventures in a differentiable wonderland
Kidger - On Neural Differential Equations
Maclaurin - Autograd - automatic differentiation with Python
Kingma, Welling - An Introduction to Variational Autoencoders
Lambert - A Little Bit of Reinforcement Learning from Human Feedback
Plaat - Learning to Play
Plaat - Deep Reinforcement Learning
Mehlig - Machine learning with neural networks
Petersen, Zech - Mathematical theory of deep learning

Genetic Programming

Poli - A Field Guide to Genetic Programming

Digital Signal Processing and Information Theory

MacKay - Information Theory, Inference, and Learning Algorithms
Smith - The Scientist and Engineer’s Guide to Digital Signal Processing
Vetterli - Foundation of Signal Processing
Prandoni et al. - Signal Processing for Communications
Frank - Control Theory Tutorial
Francis - Classical Control
Kak et al. - Principles of Computerized Tomographic Imaging
Gallager - Principles of Digital Communication
Peyre’ - The Discrete Algebra of the Fourier Transform
O’Haver - A Pragmatic Introduction to Signal Processing with applications in scientific measurements
Polyanskiy, Wu - Information Theory: From Coding to Learning, 1st Ed.
Richardson, Urbanke - Modern Coding Theory
McFee - Digital Signals Theory
Orfanidis - Applied Optimum Signal Processing

Computer Vision and Computer Graphics

Szeliski - Computer Vision: Algorithms and Applications, 2nd Ed.
Prince - Computer Vision: Models, Learning and Inference
Hyvärinen et al. - Natural Image Statistics
Solem - Programming Computer Vision with Python
Pharr et al. - Physically Based Rendering: From Theory to Implementation, 3rd Ed.
Eck et al. - Introduction to Computer Graphics
Krig - Computer Vision Metrics
McGuire - The Graphics Code
Dodgson - Image Resampling
Dunn, Parbery - 3D Math Primer for Graphics and Game Development
Phillips - Image Processing in C, 2nd Ed.
Wald - Data Fusion. Definitions and Architectures - Fusion of Images of Different Spatial Resolutions
Glassner - Principles of Digital Image Synthesis
Briggs, Carnevali - Embedding Methods for Image Search

Information Retrieval

Manning et al. - Introduction to Information Retrieval

Natural Language Processing

Jurafsky et al. - Speech and Language Processing, 3r Ed. draft
Silge et al. - Text Mining with R
Bird et al. - Natural Language Processing with Python
Eisenstein - Natural Language Processing
Liu, Lin, Sun - Representation Learning for Natural Language Processing
Bird, Klein, Loper - Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit
Koehn - Neural Machine Translation (draft)

Artificial Intelligence and Robotics

Lynch et al. - Modern Robotics - Mechanics, Planning, and Control
Murray et al. - A Mathematical Introduction to Robotic Manipulation
Nilsson - The Quest for Artificial Intelligence: A History of Ideas and Achievements
Cangelosi et al. - Cognitive Robotics
Summerfield - How to build a brain from scratch

Databases

Abiteboul - Foundation of Databases
Robinson et al. - Graph Databases

Geographic Information Systems

Lovelace et al. - Geocomputation with R
Dorman, Graser, Nowosad, Lovelace - Geocomputation with Python
Bartlein - Geographic Data Analysis (with R)
Donnelly et al. - Introduction to GIS with QGIS
Hijmans - Spatial Data Science with R
Pebesma et al. - Spatial Data Science with Applications in R
QGIS - A Gentle Introduction to GIS
Saylor Academy - Essential of Geographic Information Systems
Rey et al. - Geographic Data Science with Python
Vermeer - Geodesy
Vermeer - Physical Geodesy
Vermeer - Methods of Navigation
Vermeer et al. - Digital Aerial Mapping: A Hands-On Course
Gimond - Introduction to GIS and Spatial Analysis (with R)
Graham et al. - Geographies of Digital Exclusion
Tiberius et al. - Surveying and Mapping
INSEE - Handbook of Spatial Analysis - Theory and Application with R
Snyder - Map Projections: A Working Manual
ESRI - Understanding Map Projections
Cloud-Based Remote Sensing with Google Earth Engine
Wikle, Zammit-Mangion, Cressie - Spatio-Temporal Statistics with R
Campbell, Shin - Essentials of Geographic Information Systems
Di Biase - The Nature of Geographic Information
Longley, Goodchild, Maguire, Rhind - Geographical Information Systems: Principles, Techniques, Management and Applications, Abridged Edition
National Academies - Spatial Statistics and Digital Image Analysis
Clark - Practical Geostatistics
Hengl - A Practical Guide to Geostatistical Mapping of Environmental Variables
Hoffimann - Geospatial Data Science with Julia
Moraga - Spatial Statistics for Data Science: Theory and Practice with R

Software Engineering

Felleisen et al. - How to Design Programs
Brown et al. - The Architecture of Open Source Applications
Adkins et al. - Building Secure and Reliable Systems
Shapira et al. - Kafka: The Definitive Guide, 2nd Ed.
Kreps - I Heart Logs
Foster et al. - Cloud Computing for Science and Engineering
Fox et al. - Engineering Software as a Service: An Agile Approach Using Cloud Computing, 2nd Ed.
Burns et al. Kubernetes Up and Running, 2nd Ed.
Beyer et al. - Site Relialability Engineering: How Google Runs Production Systems
Beyer et al. - The Site Reliability Workbook: Practical Ways to Implement SRE

Operating Systems

Arpaci-Dusseau et al. - Operating Systems: Three easy Pieces
Cooper - Advanced Bash-Scripting Guide

Knowledge Representation, Semantic Web, and Linked Data

Bergman - A Knowledge Representation Practionary
Heath et al. - Linked Data: Evolving the Web into a Global Data Space
Dodds et al. - Linked Data Patterns
Hogan et al. - Knowledge Graphs

Cryptography and Information Security

Anderson - Security Engineering, 2nd Ed.
Nakov - Practical Cryptography for Developers
Van Houtven - Crypto 101
Boneh et al. - A Graduate Course in Applied Cryptography
Menezes - Handbook of Applied Cryptography
Kohel - Cryptography

Finance and Economics

Welch - Corporate Finance, 4th Ed.
Heller - The Birth of Capitalism: A 21st Century Perspective
Lengwiler - Microfoundations of Financial Economics - An Introduction to General Equilibrium Asset Pricing
The Core Team - The Economy
Bonanno - Decision Making
Bonanno - The Economics of Uncertainty and Insurance
Greenlaw et al. Principles of Economics, 2nd Ed.
Ilmanen - Expected Returns on Major Asset Classes
Fama - Foundations of Finance
BEA - NIPA Handbook: Concepts and Methods of the U.S. National Income and Product Accounts
Murphy - Understanding Money Mechanics
Knight - Risk, Uncertainty and Profit
Markowitz - Portfolio Selection: Efficient Diversiﬁcation of Investments
The Federal Reserve - The Fed Explained: What the Central Bank Does, 11th Ed.
OECD - Handbook on Constructing Composite Indicators: Methodology and User Guide
Draghi - The future of European competitiveness
James - The IMF and the European Debt Crisis
IMF - World Economic Outlook
Hermanson, Edwards, Maher - Accounting Principles: A Business Perspective
Haslem - Mutual Funds: Risk and Performance Analysis for Decision Making
Schoenmaker, Schramade - Corporate Finance for Long-Term Value
Siegel - Insights into the Global Financial Crisis
Irwin - Clashing over Commerce: A History of US Trade Policy

Macroeconomics

Doepke, Lehnert, Sellgren - Macroeconomics
Garin, Lester, Sims - Intermediate Macroeconomics

Econometrics and Quantitative Finance

Giovannini - Understanding Economic Statistics: An OECD Perspective
Puccetti - Matematica per il Corso di Economia e Management (in Italian)
Sheppard - Financial Econometrics Notes
Würtz, Setz, Chalabi, Lam, Ellis - Basic R for Finance
Würtz, Setz, Chalabi, Chen, Ellis - Portfolio Optimization with R/Rmetrics
Stachurski, Sargent - Economic Networks - Theory and Computation
Stachurski - Economic Dynamics: Theory and Computation, 2nd Ed.
Sargent et al. - Quantitative Economics with Python
Sargent et al. - Advanced Quantitative Economics with Python
Ødegaard - Financial Numerical Recipes in C++
Hanck, Arnold, Gerber, Schmelzer - Introduction to Econometrics with R
Diebold - Econometric Data Science
Heiss, Brunner - Using R, Python and Julia for Introductory Econometrics
Chen - Essentials of Technical Analysis for Financial Markets

MacKay - Sustainable Energy - without the hot air
Matthews et al. - Life Cycle Assessment: Quantitative Approaches for Decisions that Matter
Brundtland et al. - Our Common Future
Beard - Smart Grids for Dummies
Smets et al. - Solar Energy: The Physics and Engineering of Photovoltaic Conversion Technologies and Systems
Honsberg et al. - Photovoltaics
Wilcox, Kolosz, Freeman - Carbon Dioxide Removal Primer
National Academies - Negative Emissions Technologies and Reliable Sequestration
Klinger - Rare Earth Frontiers

Entrepreneurship, Project Management and Marketing

Fandrey - Academic Slide Design

Biology

Ingalls - Mathematical Modeling in Systems Biology: An Introduction
Batra et al. - The Epidemiologist R Handbook
Milo et al. - Cell Biology by the Numbers
Bonita et al. - Basic Epidemiology, 2nd Ed.
Frank - Immunology and Evolution of Infectious Disease
Frank - Dynamics of Cancer
Kellis - Computational Biology
Rost, Barbour, Stocking, Murphy - Plant Biology
Kelly - Out of Control: The New Biology of Machines, Social Systems, and the Economic World

Neuroscience

Rolls - Emotions and Decision-Making Explained
Rolls - Cerebral Cortex: Principles of Operation
Rolls, Deco - The Noisy Brain - Stochastic Dynamics as a Principle of Brain Function
Rolls - Neuroculture - On the Implications of Brain Science
Rolls - Memory, Attention, and Decision-Making: a unifying computational neuroscience approach
Rolls, Deco - The Computational Neuroscience of Vision
Rolls, Treves - Neural Networks and Brain Functions

Health and Medicine

Betts et al. - Anatomy and Physiology
World Health Organization - Manual of diagnostic ultrasound
World Health Organization - Air Quality Guidelines for Europe, 2nd Ed.

Subject Index

Physics

Classical Mechanics

Electromagnetism

Geophysics

Atmospheric Physics, Meteorology, and Climate

Inverse Theory

Oceanography

Earth Observation and Remote Sensing

Seismology

Mathematical and Computational Physics

Quantum Mechanics and Computing

Statistical Mechanics

Nuclear Physics

Medical Physics

Chemistry

Geology

Mathematics

Foundations and Logic

Algebra

Calculus

Numerical Methods

Geometry

Differential Geometry

Topology

Computational Geometry

Probability and Statistics

Stochastic Processes and Time Series

Causal Inference

Number Theory

Optimization and Linear Programming

Graph Theory

Game Theory

Category Theory

Computer Science

Algorithms and Data Structures

Distributed Systems and High Performance Computing

Computer Programming

C/C++

R

JavaScript

Haskell

Scala

Java

Python

Rust

Data Science

Data Visualization

Machine Learning

Neural Networks, Deep Learning, and Reinforcement Learning

Genetic Programming

Digital Signal Processing and Information Theory

Computer Vision and Computer Graphics

Information Retrieval

Natural Language Processing

Artificial Intelligence and Robotics

Databases

Geographic Information Systems

Software Engineering

Operating Systems

Knowledge Representation, Semantic Web, and Linked Data

Cryptography and Information Security

Finance and Economics

Macroeconomics

Econometrics and Quantitative Finance

Environmental, Social, and Governance

Entrepreneurship, Project Management and Marketing

Biology

Neuroscience

Health and Medicine