Adaptive Kernel Density Python Mapping

Go from map zero to map hero with QGIS: 'heat maps', locator maps, election maps, density maps, analysis, design + more

Go from map zero to map hero with QGIS: 'heat maps', locator maps, election maps, density maps, analysis, design + more

Master skills that are related to Python Hacking and are useful for understanding the hacking process

This book contains select chapters on support vector algorithms from different perspectives, including mathematical background, properties of various kernel functions, and several applications. The main focus of this book is on orthogonal kernel functions, and the properties of the classical kernel functions—Chebyshev, Legendre, Gegenbauer, and Jacobi—are reviewed in some chapters. Moreover, the fractional form of these kernel functions is introduced in the same chapters, and for ease of use for these kernel functions, a tutorial on a Python package named ORSVM is presented. The book also exhibits a variety of applications for support vector algorithms, and in addition to the classification, these algorithms along with the introduced kernel functions are utilized for solving ordinary, partial, integro, and fractional differential equations.

Artificial Intelligence and Data Science Algorithms in Python for Classification and Regression

Master advanced clustering, topic modeling, manifold learning, and autoencoders using Unsupervised Learning with Python!