These are the Computer Science and Mathematics books provided by Springer. This only for educational purpose. To download all of the provided Springer books you may follow scripts to download here. This includes 400+ pdfs and epubs of about 14 GB and you can also download specific books.
Download Directly in pdf format.
- The Python Workbook
- Machine Learning in Medicine - a Complete Overview
- Principles of Quantum Mechanics
- Recommender Systems
- Pharmaceutical Biotechnology
- Python Programming Fundamentals
- Object-Oriented Analysis, Design and Implementation
- Introduction to Data Science
- Game Theory
- Concise Guide to Databases
- Digital Image Processing
- Probability and Statistics for Computer Science
- Guide to Competitive Programming
- Introduction to Artificial Intelligence
- Introduction to Deep Learning
- Guide to Scientific Computing in C++
- Applied Linear Algebra
- A First Introduction to Quantum Physics
- Neural Networks and Deep Learning
- Data Science and Predictive Analytics
- Introduction to Parallel Computing
- A Beginners Guide to Python 3 Programming
- Advanced Guide to Python 3 Programming
- Introduction to Logic Circuits & Logic Design with Verilog
- LaTeX in 24 Hours
- Data Analysis
- The Data Science Design Manual
- An Introduction to Machine Learning
- Discrete Mathematics
- Mathematical Logic
- Numerical Optimization
- Probability Theory
- Time Series Analysis
- Linear and Nonlinear Programming
- Introduction to Partial Differential Equations
- Introduction to Partial Differential Equations
- Methods of Mathematical Modelling
- The Algorithm Design Manual
- Computational Physics
- Introduction to Statistics and Data Analysis
- Quantum Theory for Mathematicians
- Applied Multivariate Statistical Analysis
- Calculus With Applications
- Robotics, Vision and Control
- Probability
- Statistical Analysis and Data Display
- Probability Theory
- Statistics and Data Analysis for Financial Engineering
- Differential Equations and Their Applications
- Partial Differential Equations
- Bayesian and Frequentist Regression Methods
- Stochastic Processes and Calculus
- Guide to Discrete Mathematics
- Introduction to Time Series and Forecasting
- Multivariate Calculus and Geometry
- Statistics and Analysis of Scientific Data
- Linear Algebra
- Algebra
- Understanding Analysis
- Linear Programming
- Quantum Mechanics
- Concise Guide to Software Engineering
- Complex Analysis
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