微分積分:Calculus

アルゴリズム:Algorithms

Protected: Fundamentals of convex analysis in stochastic optimization (2) Fenchel’s dual theorem, proximity maps and strongly convex functions

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アルゴリズム:Algorithms

Overview of python Keras and examples of its application to basic deep learning tasks

Summary This section provides an overview of python Keras and specific applications to basic deep learning ...
アルゴリズム:Algorithms

Overview of combinatorial optimization and libraries and reference books for implementation

  What is a combinatorial optimization problem? Combinatorial optimization theory has been applied to many real...
Clojure

Overview of generalized linear models and their implementation in various languages

Generalized Linear Model Overview The Generalized Linear Model (GLM) is a statistical modeling and machin...
アルゴリズム:Algorithms

An overview of twitter’s recommendation algorithm

  Overviews Twitter Inc. has released a Twitter recommendation system that is getting a lot of attention. Bel...
python

Overview of automatic statement generation using Huggingface

Huggingface Huggingface is an open source platform and library for machine learning and natural language pro...
アルゴリズム:Algorithms

Example implementation for general time series analysis using R or Python

Overview of time series data analysis Time-series data is called data whose values change over time, suc...
アルゴリズム:Algorithms

Overview of LightGBM and its implementation in various languages

LightGBM Overview LightGBM is a Gradient Boosting Machine (GBM) framework developed by Microsoft, which i...
アルゴリズム:Algorithms

Time series analysis using Prophet

Prophet Overview Prophet is a time-series forecasting tool developed by Facebook that will be able to...
アルゴリズム:Algorithms

Protected: Hidden Markov model building and fully decomposed variational inference in Bayesian inference

Hidden Markov model building and fully decomposed variational inference (approximate posterior distribution, categorical distribution, Dirichlet distribution, expectation calculation, transition probability matrix, Poisson mixture model, variational inference) in Bayesian inference for digital transformation, artificial intelligence, machine learning tasks.
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