読書

Court Inside: What the California Sea Taught Me

I would like to introduce "Coat Inside: What the California Sea Taught Me" by Daniel Duane, which is currently out of print. The book is a 26-chapter essay about dropping out of society and living on the coastline of Santa Cruz, California. It will be an essay consisting of 26 chapters spent in the fall, winter, and spring.
数学:Mathematics

Decision Theory and Mathematical Decision Making Techniques

We will discuss mathematical decision-making techniques used in reinforcement learning, online prediction, and algorithms for high-speed automated stock trading. After describing the four decision strategies, I will introduce subjective probability, Bayesian theory, multiple concept theory, and supply rise theory.
Clojure

Clojure stopword removal

The following are examples of implementations of the stop word processing used in the cleansing process of natural language processing in Clojure and pyhton.
Clojure

Sorting (rearranging) data

As an introduction to data sorting, which is the basis of algorithms for the education of beginners, bubble sort, quick sort, merge sort, selection sort, and heap sort were explained. Sorting in Clojure was explained.
Clojure

Iteration and recursion (C, Java, python, Clojure)

For beginners, I will haggish the iterative operations, which is a typical feature of structured languages in various languages (C, Python, Java, JavaScript, Clojure). I will also introduce recursive programming in Clojure.
Clojure

Overview of tfidf and its implementation in Clojure

Clojure implementation of tfidf used in natural language processing
Symbolic Logic

Behavior Trees and their implementation in Unity

Overview of artificial intelligence technology used in game AI, etc., state management using behavior trees, difference from FSM
機械学習:Machine Learning

Protected: Matrix Decomposition -Extraction of relational features between two objects

Extraction of relationships by machine learning, matrix factorization approach, non-negative matrix factorization
機械学習:Machine Learning

Protected: Clustering Techniques for Asymmetric Relational Data – Probabilistic Block Model and Infinite Relational Model

Machine Learning Extraction of Relationships, Probabilistic Block Model and Infinite Relation Model
最適化:Optimization

Protected: Clustering of symmetric relational data – Spectral clustering

Extraction of relationships, knowledge extraction and prediction, spectral clustering by machine learning for graph analysis, etc.
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