pyhton

Overview and Implementation of Particle Swarm Optimization

Overview and implementation of particle swarm optimization used for digital transformation, artificial intelligence, and machine learning tasks Clojure, CAPSOS, R language, pso, pyhton, pyswarm, neural network training, parameter optimization, combinatorial optimization, robot control, pattern recognition

2023.05.18

アルゴリズム:Algorithms最適化:Optimization機械学習:Machine Learning

Protected: Static type checking with mypy in Python

Static type checking with mypy in Pyhton as a base programming technology for digital transformation, artificial intelligence , and machine learning tasks Protocol, Class, inheritance relations, Structural subtyping, Nominal subtyping, type hinting, type checking, type annotation, dynamic typing language, static typing language, gradual typing

2023.04.11

プログラミング言語:Programming Language

Differences between statically/dynamically typed languages in programming

Differences between statically/dynamically typed languages in programming used for digital transformation, artificial intelligence, and machine learning tasks Haskell, Scala, Java, type inference, JSON, automated unit testing, compilation, agile development, waterfall development, data structures, interfaces, method signatures, readability, Ruby, ease of writing, execution speed, acceleration, C, C++, Pyhton

2023.03.28

プログラミング言語:Programming Language

Overview and Implementation of the Satisfiability Determination Problem (SAT: Boolean SAtisfiability) of Propositional Logic

Overview and implementation of the satisfiability decision problem (SAT: Boolean SAtisfiability) for propositional logic, which is used in digital transformation, artificial intelligence, and machine learning tasks Clojure Rollingstones, Pyhton, PySAT, z3-solver, C++, 2-SAT, game AI, natural language processing acceleration, combinatorial optimization problem efficiency, hyperparameter optimization, computer security, automatic software specification verification, automatic chip design verification, zChaff, WalkSAT, GRASP, CryptoMiniSat, MapleSAT, Scavel, PicoSAT, MiniSAT, CaDiCaL, Lingeling, Glucose, P≠NP prediction, logic problems

2023.03.27

推論技術:inference Technology数理論理学:Mathematical logic

Protected: Application of Neural Networks to Reinforcement Learning Policy Gradient, which implements a strategy with a function with parameters.

Application of Neural Networks to Reinforcement Learning for Digital Transformation, Artificial Intelligence, and Machine Learning tasks Policy Gradient to implement strategies with parameterized functions (discounted present value, strategy update, tensorflow, and Keras, CartPole, ACER, Actor Critoc with Experience Replay, Off-Policy Actor Critic, behavior policy, Deterministic Policy Gradient, DPG, DDPG, and Experience Replay, Bellman Equation, policy gradient method, action history)

2023.02.16

アルゴリズム:Algorithmsグラフ理論スパースモデリングマルチエージェントシステム幾何学:Geometry強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Math, Music and Computers

Math, music and computers (algorave, live-coding, supercollider, synthesizers, overtone, Clojure, pyhton, FoxDot, generative art)

2023.01.03

音楽:Music

Protected: DNN for text and sequences with python and Keras (3) Advanced use of recurrent neural networks(GRU)

Analysis of sequence data by GRU with pyhton/keras used for digital transformation and artificial intelligence tasks and improvement by recurrent dropout and recurrent layer stacking

2021.11.11

python最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning自然言語処理:Natural Language Processing

Protected: Deep learning for computer vision with Python and Keras (2) Improving CNNs with small amounts of data through data expansion

Methods to improve CNNs for small amounts of data using pyhton/Keras for digital transformation and artificial intelligence tasks (improving overtraining by data expansion)

2021.11.06

python最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning画像認識技術

Protected: Deep Learning for Computer Vision with Python and Keras(1) – Convolution and Pooling

Overview of convolution and pooling in pyhton/keras/CNN for image recognition using deep learning for digital transformation and artificial intelligence tasks.

2021.11.05

python最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning画像認識技術