The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our WorldBasic Books, 22 sep 2015 - 352 pagina's Recommended by Bill Gates A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible. |
Inhoudsopgave
The Master Algorithm | |
Humes Problem of Induction | |
How Does Your Brain Learn? | |
Evolution Natures Learning Algorithm | |
In the Church of the Reverend Bayes | |
You Are What You Resemble | |
Overige edities - Alles bekijken
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will ... Pedro Domingos Gedeeltelijke weergave - 2015 |
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will ... Pedro Domingos Geen voorbeeld beschikbaar - 2018 |
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will ... Pedro Domingos Geen voorbeeld beschikbaar - 2015 |
Veelvoorkomende woorden en zinsdelen
answer apply attributes Bayes Bayesian networks becomes better brain build called cancer cause cell Chapter clusters combine complex concepts course curve decide decision dierent don’t eect engineering everything evolution example face fact friends function future genes genetic give given goes gure hand human images important inference input intelligence it’s keep knowledge laws learner learning algorithms less logic look machine learning Markov Master Algorithm means million nature networks neural neurons never objects once optimization perceptron perhaps positive possible predict probability problem question reason result robot rule scientists similar simple single solve starting step structure symbolists theorem theory there’s things thousand tion tree turn understand University weights