IOT技術:IOT Technology Time series data analysis
Time Series Data Learning
Overview
Time-series data is called data whose values change over time, such ...
確率・統計:Probability and Statistics
IOT技術:IOT Technology オンライン学習 Protected: Planning Problems (2) Implementation of Dynamic Programming (Value Iterative Method and Measure Iterative Method)
Implementation of Dynamic Programming (Value Iteration and Policy Iteration) for Planning Problems as Reinforcement Learning for Digital Transformation , Artificial Intelligence and Machine Learning Tasks
推論技術:inference Technology Statistical Causal Inference and Causal Search
Statistical Causal Inference and Causal Search
Overview
When using machine learning, it is important to consider...
強化学習 Protected: Planning Problems(1) – Approaches Using Dynamic Programming and Theoretical Underpinnings
Reinforcement learning by planning problems (dynamic programming and linear programming) for sequential decision problems in known environments used for digital transformation , artificial intelligence and machine learning tasks.
オンライン学習 Protected: Evaluating the performance of online learning(Perceptron, Regret Analysis, FTL, RFTL)
Perceptron and Riglet Analysis (FTL, RFTL) for evaluating online learning used for digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習 Protected: Advanced online learning (4) Application to deep learning (AdaGrad, RMSprop, ADADELTA, vSGD)
Application to online learning in AdaGrad, RMSprop, and vSGD used for digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習 Protected: Advanced online learning (3) Application to deep learning (mini-batch stochastic gradient descent, momentum method, accelerated gradient method)
Improving computational efficiency by applying mini-batch stochastic gradient descent, momentum, and accelerated gradient methods to deep learning for digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習 Protected: Advanced Online Learning (2) Distributed Parallel Processing(Parallelized mini-batch stochastic gradient method, IPM, BSP, SSP)
Distributed parallel processing of online learning (parallelized mini-batch stochastic gradient method, IPM, BSP, SSP) to efficiently process large scale data for digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習 Machine Learning Professional Series “Online Prediction” Reading Memo
Online prediction, which is machine learning that combines prediction and decision making problems used in digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習 Protected: Advanced online learning (1) High accuracy Approach (Perceptron, PA, PA-I, PA-II, CW, AROW, SCW)
Introduction to various methods for improving the accuracy of online learning for digital transformation , artificial intelligence and machine learning tasks (Perceptron, PA, CW, AROW, SCW)