幾何学:Geometry

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Challenges and implementation of achieving 100% reproducibility for risk task response

What is a 100% Recall in machine learning? In machine learning tasks, recall is the main metric used fo...
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Protected: Neural Networks as Applied Models of Bayesian Inference

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Protected: Logistic regression as an applied model of Bayesian inference

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Protected: Tensor Decomposition and Recommendation as Applied Models of Bayesian Inference

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Protected: Inference by Gibbs sampling in a topic model as an applied model of Bayesian inference.

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Protected: Overview of the topic model as an applied model of Bayesian inference and application of variational inference

Overview of topic models as applied Bayesian inference models for digital transformation, artificial intelligence, and machine learning tasks and application of variational inference variational inference algorithms, Dirichlet distribution, categorical distribution, LDA, topic models in multimedia
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Protected: Hidden Markov model building and structured variational inference in Bayesian inference

Hidden Markov model building and structured variational inference (mini-batch, structured variational inference, fully decomposed variational inference, additional learning, underflow, message passing, exact inference algorithms, forward-backward algorithms, approximate distribution of parameters) in Bayesian inference for digital transformation, artificial intelligence, machine learning tasks.
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Protected: Reinforcement learning application areas (2)

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Protected: Reinforcement learning application areas (1)Behavior Optimization

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python

About ATTENTION in Deep Learning

About "Attention Is All You Need" "Attention Is All You Need" will be the paper that proposed a neural netwo...
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