Search
Search Results
-
Linear Algebra and Optimization for Machine Learning A Textbook
This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout the book....
-
Algebra and Geometry with Python
This book teaches algebra and geometry. The authors dedicate chapters to the key issues of matrices, linear equations, matrix algorithms, vector...
-
Data Science An Introduction to Statistics and Machine Learning
This textbook provides an easy-to-understand introduction to the mathematical concepts and algorithms at the foundation of data science. It covers...
-
Elements of Dimensionality Reduction and Manifold Learning
Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for...
-
Linear Algebra for Computational Sciences and Engineering
This book presents the main concepts of linear algebra from the viewpoint of applied scientists such as computer scientists and engineers, without...
-
Foundations of Vector Retrieval
This book presents the fundamentals of vector retrieval. To this end, it delves into important data structures and algorithms that have been...
-
Machine Learning Methods
This book provides a comprehensive and systematic introduction to the principal machine learning methods, covering both supervised and unsupervised...
-
Concise Guide to Quantum Machine Learning
This book offers a brief but effective introduction to quantum machine learning (QML). QML is not merely a translation of classical machine learning...
-
Numerical Methods Using Kotlin For Data Science, Analysis, and Engineering
This in-depth guide covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and...
-
Numerical Methods Using Java For Data Science, Analysis, and Engineering
Implement numerical algorithms in Java using NM Dev, an object-oriented and high-performance programming library for mathematics.You’ll see how it...
-
Vector Analysis for Computer Graphics
This second edition has been completely restructured, resulting in a compelling description of vector analysis from its first appearance as a...
-
Statistical Learning with Math and Python 100 Exercises for Building Logic
The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience....
-
Deep Learning with Python Learn Best Practices of Deep Learning Models with PyTorch
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and...
-
Practical Business Analytics Using R and Python Solve Business Problems Using a Data-driven Approach
This book illustrates how data can be useful in solving business problems. It explores various analytics techniques for using data to discover hidden...
-
Applied Deep Learning with TensorFlow 2 Learn to Implement Advanced Deep Learning Techniques with Python
Understand how neural networks work and learn how to implement them using TensorFlow 2.0 and Keras. This new edition focuses on the fundamental...
-
Computational Methods for Deep Learning Theoretic, Practice and Applications
Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively...
-
Computer Vision Algorithms and Applications
Computer Vision: Algorithms and Applicationsexplores the variety of techniques used to analyze and interpret images. It also describes challenging...
-
Deep Generative Modeling
This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning. Moreover, it goes beyond typical...
-
Deep Learning-Based Face Analytics
This book provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present...
-
Mathematical Foundations of Big Data Analytics
In this textbook, basic mathematical models used in Big Data Analytics are presented and application-oriented references to relevant practical issues...