The phrase ‘the meaning of life’ for many seems a quaint notion fit for satirical mauling by Monty Python or Douglas Adams. But in this spirited, stimulating, and quirky enquiry, famed critic Terry Eagleton takes a serious if often amusing look at the question and offers his own surprising answer.
This volume of specially commissioned essays is a critical introduction to the psychology of Carl Jung, one of the founders of psychoanalysis. Jung broke with Freud and developed his own theories which he called ‘analytical psychology’. The essays set Jung in the context of his own time, outline the practice and theory of Jungian psychology and show how Jungians continue to question and evolve his thinking to fit the post-modern, multi-cultural world of contemporary psychoanalysis. Andrew Samuels’s introduction gives an appreciation of Jung’s work and discusses the three approaches to analytical psychology. The Companion includes a full chronology of his life and work, reading lists, a case study and a glossary. It is an indispensible reference tool for beginning students and specialists, written by an international team of Jungian analysts and scholars from various disciplines.
Visual masking is a technique used in cognitive research to understand pre-conscious processes (e.g., priming), consciousness, visual limits, and perception issues associated with psychopathology. This work is a short format review of research using visual masking: how its been used, and what these experiments have discovered. Its a strategic fit to our other cognitive psychology titles.
A machine is said to learn when its , improves with experience. Learning requires algorithms and programs that capture data and ferret out the interesting or useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill needed by many.,
Machine Learning in Action is a clearly written tutorial for developers. It avoids academic language and takes you straight to the techniques you’ll use in your day-to-day work. Many (Python) examples present the core algorithms of statistical data processing, data analysis, and data , in code you can reuse. You’ll understand the concepts and how they fit in with tactical tasks like classification, forecasting, recommendations, and higher-level features like summarization and simplification.
