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AIMA gives detailed information about the working of algorithms in AI. The book's chapters span from classical AI topics like searching algorithms and first-order logic, propositional logic and probabilistic reasoning to advanced topics such as multi-agent systems, constraint satisfaction problems, optimization problems, artificial neural networks, deep learning, reinforcement learning, and ...
Artificial Intelligence (AI) is a university textbook on artificial intelligence, written by Patrick Henry Winston. It was first published in 1977, and the third edition of the book was released in 1992. [ 1 ]
In The Christian Science Monitor, author Barbara Spindel states the "lucid", "clear-eyed" and "fascinating" book does a good job documenting that artificial general intelligence is nowhere near, and believes that "many readers will be reassured to know that we will not soon have to bow down to our computer overlords." Spindel expresses surprise ...
In the context of AI, it is particularly used for embedded systems and robotics. Libraries such as TensorFlow C++, Caffe or Shogun can be used. [1] JavaScript is widely used for web applications and can notably be executed with web browsers. Libraries for AI include TensorFlow.js, Synaptic and Brain.js. [6]
Data is typically distinguished in spatial data and time-series data, the former can be things like images, maps, graphs, etc. the latter can be e.g. stock-price or a voice recording. Document AI combines text data, which has a time dimension, with other types of data, such as the position of an address in a business letter, which is spatial.
Leading textbook company Pearson has outfitted its digital textbooks—specifically 50 science titles, such as Intro to Biology and Intro to Chemistry—with generative AI study tools. As of this ...
Center for Applied Internet Data Analysis Cuff-Less Blood Pressure Estimation Dataset Cleaned vital signals from human patients which can be used to estimate blood pressure. 125 Hz vital signs have been cleaned. 12,000 Text Classification, regression 2015 [156] [157] M. Kachuee et al. Gas Sensor Array Drift Dataset
ML involves the study and construction of algorithms that can learn from and make predictions on data. [3] These algorithms operate by building a model from a training set of example observations to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions.