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 ...
線形代数:Linear Algebra
アルゴリズム:Algorithms 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.
アルゴリズム:Algorithms Protected: Research Trends in Deep Reinforcement Learning: Meta-Learning and Transfer Learning, Intrinsic Motivation and Curriculum Learning
Research trends in deep reinforcement learning for digital transformation, artificial intelligence, and machine learning tasks: meta-learning and transfer learning, intrinsic motivation and curriculum learning automatic curriculum generation, automatic task decomposition, task difficulty adjustment, intrinsic reward, robot domain transformation, robot domain transformation, simulator to simulator transfer learning, BERT, Metric/Representation Base, Memory/Knowledge Base, active learning, meta-learning, and robot domain transformation) Robot domain transformation, transfer learning from simulators, BERT, Model-Agnostic Meta-Learning, Active Learning, Metric/Representation Base, Memory/Knowledge Base, Weigh Base, and Learning to Optimize