自然言語処理:Natural Language Processing

Clojure

Chatbots and Question&Answer Technology

Overview of chubbot technology used in digital transformation , artificial intelligence, etc., from a business perspective, as well as question-and-answer systems that combine natural language processing, deep learning, and knowledge network technologies
微分積分:Calculus

Protected: Topic models – maximum likelihood estimation, variational Bayesian estimation, estimation by Gibbs sampling

Maximum likelihood, variational Bayesian, and Gibbs sampling estimation of topic models for digital transformation , artificial intelligence , and natural language processing tasks.
機械学習:Machine Learning

Protected: Higher-order relational data – an overview of tensor data processing

Tensor data processing to analyze relationships between three or more objects for use in digital transformation and artificial intelligence tasks.
微分積分:Calculus

Protected: Estimating the number of topics in a topic model – Dirichlet process, Chinese restaurant process, stick-folding process

A topic model using Dirichlet process, Chinese restaurant process, and stick-folding process for digital transformation and artificial intelligence tasks.
微分積分:Calculus

Protected: Application of Topic Models to Information Other Than Documents – Application to Image Data and Graph Data (Stochastic Block Model, Mixed Member Probabilistic Block Model)

Topic models for image and graph data using stochastic block models for digital transformation and artificial intelligence tasks.
微分積分:Calculus

Protected: Extension of topic models (adding structure to topics) Correlation topic model, slingshot distribution model with hierarchical structure, probabilistic latent semantic visualization with low-dimensional spatial structure

Overview of topic models with structure in correlated topics used in digital transformation and artificial intelligence tasks (correlated topic model, slingshot distribution model with hierarchical structure, probabilistic latent meaning visualization with low-dimensional spatial structure)
微分積分:Calculus

Protected: Extending topic models (using other information as well) (2) Noisy correspondence topic model, author topic model, topic tracking model

Among topic models that rely on auxiliary information for digital transformation and artificial intelligence tasks, we will discuss noisy topic models, author topic models, and topic tracking models.
推論技術:inference Technology

Protected: Extending the topic model (using other information) (1) Combined topic model and corresponding topic model

Create a topic model with auxiliary information to be used for digital transformation and artificial intelligence tasksJoining / Corresponding Topic Model Overview
機械学習:Machine Learning

Topic Model Theory and Implementation

A topic model is a probability generation model for extracting topics from sentences, which is one of the natural language processing technologies used in digital transformation and artificial intelligence tasks.
地理空間情報処理

Machine Learning Professional Series – Relational Data Learning Post-Reading Notes

Overview of relational data learning to extract the meaning and knowledge behind information used in digital transformation , artificial intelligence , and machine learning tasks.
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