You can develop the foundational skills you need to advance to building neural networks and creating more complex functions through the Python and R programming languages. Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. Machine Learning A-Z course from zero with Python, Kaggle, Pandas and Numpy for data analysis with hands-on examples The deepest is formed by the C+ + library functions for computing with real and complex numbers.Ī list of errata can be found on the author’s personal webpage.Welcome to the ” Machine Learning & Data Science with Python, Kaggle & Pandas “ Course Examples are included to demonstrate their use. Rather than describing programs implementing specific numerical techniques to solve specific applica tion problems, the book constructs reusable tools with which you can implement many techniques for solving broad classes of problems.
What's new here is the emphasis on software tools and on OOP techniques for handling vectors, polynomials, and matrices.
The book is heavily weighted toward software development. On this foundation routines are constructed for solving nonlinear equations, linear and nonlinear systems of equations, and eigenvalue problems. The most basic include details of computation with floating-point real and complex numbers mathematical functions in the C+ + Library and a general OOP framework for vector, polynomial, and matrix algebra. At the core of most scientific or engineering application programs are some of the concepts and techniques presented here. The toolkit and its description and background discussions cover the most fundamental aspects of numerical analysis. However, the book describes few features specific to that product. 02, for IBM-compatible personal computers. Its development environment is the Borland International, Inc.
0, and makes essential use of that language's Object-Oriented Programming (OOP) features.
This book describes the design, construction, and use of a numerical analysis software toolkit.