IOT技術:IOT Technology Weather Forecasting and Data Science
Weather forecasting and data assimilation for simulation and data science integration for digital transformation, artificial intelligence, and machine learning task utilization
時系列データ解析
IOT技術:IOT Technology IOT技術:IOT Technology Protected: Time series data analysis (3)Filtering of nonlinear and non-Gaussian state space models (e.g. particle filter)
Filtering and smoothing of nonlinear and non-Gaussian state-space models using particle filters in the analysis of time-series data with state-space models for digital transformation, artificial intelligence, and machine learning tasks
Stream Data Processing Protected: Simulation, Data Assimilation, and Emulation
Fusion of extrapolation (deduction) estimation using simulation and interpolation (induction) estimation using machine learning (simulation assimilation and emulation using DNN, etc.) for digital transformation, artificial intelligence and machine learning tasks
Stream Data Processing Reading notes for Iwanami Data Science Series “Time Series Analysis
Summary
Time-series data is called data whose values change over time, such as stock prices, temperature...
IOT技術:IOT Technology Protected: Differences between hidden Markov models and state-space models and parameter estimation for state-space models
Differences between state-space models, Bayesian models, and hidden Markov models used in digital transformation, artificial intelligence, and machine learning tasks, and parameter estimation for state-space models
IOT技術:IOT Technology Protected: Time series data analysis (2) Filtering Sequential estimation of state and seasonal adjustment model
Prediction of time series using state-space models of time series data utilized in digital transformation, artificial intelligence, and machine learning; interpolation, parameter estimation, and analysis of store sales using component decomposition and standard seasonal adjustment models.
Stream Data Processing Protected: Time Series Data Analysis (1) – State Space Model
Overview of various state-space models linear and Gaussian state-space models, AR models, autoregressive and moving average ARMA models, component decomposition models, and time-varying coefficient models) for time series data analysis used in digital transformation, artificial intelligence, and machine learning tasks
IOT技術:IOT Technology Protected: Structural regularization learning with submodular optimization (1) Regularization and p-norm review
Review of sparse modeling, regularization and p-norm to consider structural regularization learning with submodular optimization, an optimization technique for discrete information for digital transformation, artificial intelligence and machine learning tasks
IOT技術:IOT Technology Protected: Maximum Flow and Graph Cut (4) Graphically Representable Submodular Functions
Maximum flow algorithms and pre-flow push methods in graphically representable submodular functions for submodular optimization, an optimization approach for discrete information utilized in digital transformation, artificial intelligence, and machine learning tasks
Stream Data Processing Protected: PF for fast processing of streamed data and large amounts of data: Apache Spark Overview
Overview of ApacheSpark, an open source platform used for digital transformation, artificial intelligence, and machine learning tasks to process streamed and massive data at high speed