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...
幾何学:Geometry
幾何学:Geometry 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 Overview of the topic model and various implementations
Topic Model Overview
The topic model will be a statistical model for automatically extracting topics (them...