RNN | Deus Ex Machina

Protected: Implementation of two approaches to improve environmental awareness, a weak point of deep reinforcement learning.

Implementation of two approaches to improve environment awareness, a weakness of deep reinforcement learning used in digital transformation, artificial intelligence, and machine learning tasks (inverse predictive, constrained, representation learning, imitation learning, reconstruction, predictive, WorldModels, transition function, reward function Weaknesses of representation learning, VAE, Vision Model, RNN, Memory RNN, Monte Carlo methods, TD Search, Monte Carlo Tree Search, Model-based learning, Dyna, Deep Reinforcement Learning)

2023.04.27

アルゴリズム:Algorithmsグラフ理論スパースモデリングマルチエージェントシステム幾何学:Geometry強化学習微分積分:Calculus数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics

Protected: Overview of Weaknesses and Countermeasures in Deep Reinforcement Learning and Two Approaches to Improve Environment Recognition

An overview of the weaknesses and countermeasures of deep reinforcement learning utilized in digital transformation, artificial intelligence, and machine learning tasks and two approaches of improving environmental awareness Mixture Density Network, RNN, Variational Auto Encoder, World Modles, Expression Learning, Strategy Network Compression, Model Free Learning, Sample-Based Planning Model, Dyna, Simulation-Based, Sample-Based, Gaussian Process, Neural Network, Transition Function, Reward Function) World Modles, Representation Learning, Strategy Network Compression, Model-Free Learning, Sample-Based Planning Model, Dyna, Simulation-Based, Sample-Based, Gaussian Process, Neural Network, Transition Function, Reward Function, Simulator , learning capability, transition capability

2023.04.13

アルゴリズム:Algorithmsグラフ理論スパースモデリング幾何学:Geometry強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: DNN for text and sequences with Python and Keras (2) Application of SimpleRNN and LSTM

RNN and LSTM for text/sequence information using python/keras for digital transformation and artificial intelligence tasks

2021.11.10

python最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning自然言語処理:Natural Language Processing

Protected: Applying Deep Learning to Speech Recognition

Overview of neural network applications (TDNN, RNN, CNN) and deep learning applications (LSTM, CTC) for speech recognition technology used in digital transformation and artificial intelligence tasks

2021.10.07

機械学習:Machine Learning深層学習:Deep Learning音声信号認識技術

Protected: Natural Language Processing with Deep Learning (1) Data Representation Model

Overview of natural language processing by deep learning, one-hot vector, distributed representation

2021.05.08

機械学習:Machine Learning深層学習:Deep Learning自然言語処理:Natural Language Processing