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scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
TensorFlow serves as a core platform and library for machine learning. TensorFlow's APIs use Keras to allow users to make their own machine-learning models. [ 41] In addition to building and training their model, TensorFlow can also help load the data to train the model, and deploy it using TensorFlow Serving.
Google Brain was a deep learning artificial intelligence research team under the umbrella of Google AI, a research division at Google dedicated to artificial intelligence. Formed in 2011, it combined open-ended machine learning research with information systems and large-scale computing resources. [ 1] It created tools such as TensorFlow, which ...
Θ ( n × n ! ) {\displaystyle \Theta (n\times n!)} In computer science, bogosort[ 1][ 2] (also known as permutation sort and stupid sort[ 3]) is a sorting algorithm based on the generate and test paradigm. The function successively generates permutations of its input until it finds one that is sorted. It is not considered useful for sorting ...
Random optimization. Random optimization (RO) is a family of numerical optimization methods that do not require the gradient of the problem to be optimized and RO can hence be used on functions that are not continuous or differentiable. Such optimization methods are also known as direct-search, derivative-free, or black-box methods.
Anki ( US: / ˈɑːŋki /, UK: / ˈæŋki /; Japanese: [aŋki]) is a free and open-source flashcard program. It uses techniques from cognitive science such as active recall testing and spaced repetition to aid the user in memorization. [ 4][ 5] The name comes from the Japanese word for "memorization" ( 暗記 ). [ 6] The SM-2 algorithm, created ...
In machine learning, hyperparameter optimization[ 1] or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a parameter whose value is used to control the learning process. Hyperparameter optimization determines the set of hyperparameters that yields an optimal model which minimizes a ...
A Google spokesperson declined to comment. The verdict, delivered last week, held that Google violated antitrust law, spending billions of dollars to create an illegal monopoly and become the ...