A Business Analyst’s Introduction to Business Analytics
A First Course in Monte Carlo Methods
Advanced Calculus For Data Science
Algorithmic High-Dimensional Robust Statistics
Algorithms (Sedgewick, Wayne )
Algorithms for Modern Hardware
Algorithms for Reinforcement Learning
Alice’s Adventures in a differentiable wonderland
An infinite descent into pure mathematics
An Introduction to the Analysis of Algorithms
An Introduction to Graph Theory
An Introduction to Quantum Computing
An Introduction to Statistical Learning
An Owner's Guide to the Human Genome
Annotated Algorithms in Python
Applied Causal Inference Powered by ML and AI
Artificial Intelligence: Foundations of Computational Agents
Bayesian models of perception and action
Calculus: early transcendentals
Competitive Programmer's Handbook
Computational and Inferential Thinking
Computational Discovery on Jupyter
Computational Topology for Data Analysis
Computer Vision: Algorithms and Applications
Data Science and Machine Learning
Data Structures and Information Retrieval in Python
Differential Equations (Chasnov)
Distributional Reinforcement Learning
Earth Engine User Guide: Python
Elements of Applied Functional Analysis
Equivariant and Coordinate Independent Convolutional Networks
Feedback Systems: An Introduction for Scientists and Engineers
Forecasting: Principles and Practice
Foundation Models for Natural Language Processing
Foundations of Vector Retrieval
Functional Data Structures and Algorithms
Fundamentals of Numerical Computation
Geospatial Data Science with Leafmap
Handbook of Regression Modeling in People Analytics
Hands-On Machine Learning with R
Hands-On Mathematical Optimization with Python
How to Think Like a Computer Scientist
Human-Robot Interaction — An Introduction
Information Theory: From Coding to Learning
Interpretable Machine Learning
Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares
Introduction to Automata Theory, Languages, and Computation
Introduction to Autonomous Robots
Introduction to Causal Inference
Introduction to Classical and Quantum Computing
Introduction to Control Systems
Introduction to Differential Geometry
Introduction to Financial Engineering with R
Introduction to General Relativity, Black Holes and Cosmology
Introduction to Information Theory
Introduction to Linear Algebra
Introduction to Machine Learning Interviews Book
Introduction to Modern Cryptography
Introduction to Partial Differential Equations
Introduction to Probability for Computing
Introduction to Probability, Statistics, and Random Processes
Introduction to Smooth Manifolds
Introduction to Modern Statistics
Introduction to Theoretical Computer Science
Learning Theory and Kernel Machines
Lecture Notes on Financial Mathematics
Linear Algebra, Theory And Application
Machine Learning - A First Course for Engineers and Scientists
Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory
Mathematics for Machine Learning
Mechanical Engineering Methods
Mixtape: Causal Inference for Statistics
Modeling and Simulation in Python
Modern Data Science with R (3nd Edition)
Modern Statistics for Modern Biology
Multi-Agent Reinforcement Learning
Notes on Continuous Optimization
Numerical methods for partial differential equations
Numerical Methods for Scientific Computing
Numerical Methods for Scientists and Engineers
Ordinary Differential Equations and Dynamical Systems
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications
Partial Differential Equations
Pattern Recognition and Machine Learning
Probabilistic Machine Learning Book 1
Probabilistic Machine Learning Book
Probability & Statistics with Applications to Computing
Probability: Theory and Examples
Probability Theory: The Logic of Science
Problem Solving with Algorithms and Data Structures using Python
Qualitative Dynamics and Chaos
Quantitative Economics with Python
Quantum Computing for Computer Scientists
Random Matrix Methods for Machine Learning
Reinforcement Learning: An Introduction
Reinforcement Learning for Finance
Speech and Language Processing
Software Technical Writing: A Guidebook
Spatial Statistics for Data Science
State Space Models: A Modern Approach
Stochastic Differential Equations: An Introduction with Applications in Population Dynamics Modeling
Technical Analysis with R (Second Edition)
The Effect: An Introduction to Research Design
The Elements of Differentiable Programming
The Mathematical Engineering of Deep Learning