機械学習:Machine Learning

オンライン学習

Protected: Reinforcement Learning with Function Approximation (2) – Function Approximation of Value Functions (For Online Learning)

Theory of function approximation online methods gradient TD learning, least-squares based least-squares TD learning (LSTD), GTD2)for reinforcement learning with a huge number of states used in digital transformation , artificial intelligence , and machine learning tasks, and regularization with LASSO.
強化学習

Protected: Reinforcement Learning with Function Approximation (1) – Function Approximation of Value Functions (Batch Learning Case)

Function approximation in the case of batch learning of value functions to deal with a huge number of states in reinforcement learning for digital transformation, artificial intelligence, and machine learning tasks.
推論技術:inference Technology

Protected: Modeling of time series and spatial data (1)(Dynamic linear model)

Bayesian modeling of temporal and spatial models with a focus on dynamic linear models and evaluation using MCMC
IOT技術:IOT Technology

Protected: Model-based reinforcement learning(Sparse sampling, UCT, Monte Carlo search tree)

Model-based reinforcement learning (sparse sampling, UCT, Monte Carlo search trees) used for digital transformation artificial intelligence , and machine learning tasks.
アルゴリズム:Algorithms

Machine Learning Professional Series Bayesian Deep Learning Reading Notes

Machine Learning Professional Series Bayesian Deep Learning Reading Notes Writing a reading note from "Bayesi...
グラフ理論

Structural Learning

  About Structural Learning Learning the structure that data has is important for interpreting what the data is a...
微分積分:Calculus

Machine Learning Professional Series “Continuous Optimization for Machine Learning” Reading Memo

Summary Continuous optimization in machine learning is a method for solving optimization problems in which varia...
IOT技術:IOT Technology

Protected: Model-free reinforcement learning (2) – Method iteration (Q-learning, SARSA, Actor-click method)

Value iteration methods Q-learning, SARSA, Actor-critic methods to model-free reinforcement learning for digital transformation , artificial intelligence and machine learning tasks.
python

Machine Learning Startup Series “Reinforcement Learning in Python”

Summary Reinforcement learning is a field of machine learning in which an agent, which is the subject of lear...
オンライン学習

Protected: Model-free reinforcement learning(1) – Value iteration methods (Monte Carlo, TD, TD(λ))

Application of value iterative methods (Monte Carlo, TD, TD(λ)) to model-free reinforcement learning used in digital transformation , artificial intelligence , and machine learning.
タイトルとURLをコピーしました