Posts
 |
| Photo: Storyblocks.com |
 |
| Exploring Mathematics An Engaging Introduction to Proof |
The end-of-chapter exercises and projects provide students with opportunities to confirm their understanding of core material, learn new concepts, and develop mathematical creativity.
- Mixes the creativity and rigor that is essential to conducting mathematical enquiry and includes model proofs as well as a range of accessible topics, such as Fibonacci numbers and games, to encourage students to explore and to build intuition and background
- Engages the reader thanks to in-text exercises with complete solutions and robust hints included in an appendix and helps students develop the skill of frequently interrogating the definitions, examples, and arguments presented
- Offers students the opportunity to practice their mathematical writing skills in response to sometimes challenging questions, and with less emphasis on formal logic and rote proof-writing exercises
An Introduction to Indian Philosophy
 |
| An Introduction to Indian Philosophy |
Read more...
The Psychology of Musical Development
 |
| The Psychology of Musical Development |
With an emphasis on practical applications throughout, this book will be essential reading for students and scholars of music psychology, developmental psychology, music education and music therapy.
- Advances the study of musical development, a field which has expanded beyond recognition in the last thirty years
- Provides a state-of-the-art summary of theories in this field, including cognitive stage models, neuroscience, socio-cultural theory, self-theory, ecological models and social cognitive approaches
- Devotes attention to practical applications of music psychology, especially in child development, music education, and health and well-being
Probability and Computing
Randomization and Probabilistic Techniques in Algorithms and Data Analysis
 |
| Probability and Computing Randomization and Probabilistic Techniques in Algorithms and Data Analysis |
This book provides an indispensable teaching tool to accompany a one- or two-semester course for advanced undergraduate students in computer science and applied mathematics.
- Contains all the background in probability needed to understand many subdisciplines of computer science
- Includes new material relevant to machine learning and big data analysis, enabling students to learn new, up-to-date techniques and applications
- Newly added chapters and sections cover the normal distribution, sample complexity, VC dimension, naïve Bayes, cuckoo hashing, power laws, and the Lovasz Local Lemma
- Many new exercises and examples, including several new programming-related exercises, provide students with excellent training in problem solving
Source: Cambridge University Press
