幾何学:Geometry

幾何学:Geometry

Cross-Entropy Loss

Overview of  Cross-Entropy Loss Cross-Entropy Loss (Cross-Entropy Loss) is one of the common loss functions use...
アルゴリズム:Algorithms

Overview of Bayesian Structural Time Series Models and Examples of Application and Implementation

Bayesian Structural Time Series Models Bayesian Structural Time Series Model (BSTS) is a type of statisti...
アルゴリズム:Algorithms

Why Reinforcement Learning? Application Examples, Technical Issues and Solution Approaches

  Introduction Reinforcement learning is another aspect of OpenAI, which is famous for chatGPT. the heart of ...
グラフ理論

Overview of Variational Bayesian Learning and Various Implementations

About Variational Methods in Machine Learning Variational methods (Variational Methods) are used to find the op...
IOT技術:IOT Technology

Overview and implementation of image recognition systems

Image Recognition System Overview An image recognition system will be a technology in which a computer analy...
アルゴリズム:Algorithms

Overview of mixed integer optimization and its algorithm and implementation in python

  Mixed-Integer Optimization Mixed integer optimization is a type of mathematical optimization and refers...
アルゴリズム:Algorithms

Protected: Model Building and Inference in Bayesian Inference – Overview and Models of Hidden Markov Models

Model building and inference of Bayesian inference for digital transformation, artificial intelligence, and machine learning tasks - Overview of hidden Markov models and models eigenvalues, hyperparameters, conjugate prior, gamma prior, sequence analysis, gamma distribution, Poisson distribution, mixture models graphical model, simultaneous distribution, transition probability matrix, latent variable, categorical distribution, Dirichlet distribution, state transition diagram, Markov chain, initial probability, state series, sensor data, network logs, speech recognition, natural language processing
アルゴリズム:Algorithms

Overview of Causal Forest and examples of application and implementation in R and Python

  Causal Forest Causal Forest is a machine learning model for estimating causal effects from observed d...
アルゴリズム:Algorithms

Overview of graph neural networks and examples of application and implementation in python

Graph Neural Networks A graph neural network (GNN) is a type of neural network for data with a graph struc...
アルゴリズム:Algorithms

Protected: Neural Networks as Applied Models of Bayesian Inference

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