深層学習:Deep Learning

Protected: Mathematical Elements in Neural Networks(1) – Manipulating Tensors with numpy, etc.

Mathematical aspects of tensor manipulation using Numpy and others as a basis for performing deep learning used in digital transformation and artificial intelligence tasks.

2021.10.28

python最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning

Protected: Hello World of Neural Networks, Implementation of Handwriting Recognition with MNIST Data

On the Implementation with python and Keras of HelloWorld and handwriting recognition of neural networks in machine learning using neural nets for digital transformation and artificial intelligence tasks.

2021.10.27

python最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning

History of AI and Deep Learning

Basic definitions of artificial intelligence, machine learning, and deep learning used in digital transformation and artificial intelligence tasks, and characteristics of deep learning.

2021.10.26

python最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning

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: Instance recognition and retrieval (1) Instance retrieval using BoVW

Instance recognition and image retrieval technology based on image recognition technology used in digital transformationand artificial intelligence

2021.10.04

推論技術:inference Technology検索技術:Search Technology機械学習:Machine Learning深層学習:Deep Learning画像認識技術

Protected:

Overview of noise reduction techniques to improve speech recognition for digital transformation and artificial intelligence tasks (additive noise, multiplicative noise and active noise control, parallel model coupling, PMC, factorial HMM)

2021.10.03

機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics音声信号認識技術

Protected: Application of Hidden Markov Models to Speech Recognition

Overview of hidden Markov models (HMMs) for speech recognition for use in digital transformation and artificial intelligence tasks (Baum-Welch algorithm, Viterbi algorithm, EM algorithm, CDHMM).

2021.09.30

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

Protected: Speech Recognition: Overview and Application of Dynamic Programming (DP)

Overview of speech recognition techniques that can be used for digital transformation and artificial intelligence tasks, and recognition techniques using dynamic programming (DP) methods (DP matching, beam search, word spotting, two-stage DP matching, level building method, one-pass DP matching)

2021.09.29

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

Protected: Speech Analysis:AD transform, analytical window, Fourier transform and vector quantization

Pre-processing of speech recognition for digital transformation and artificial intelligence tasks, from AD conversion to feature extraction and vector quantization

2021.09.28

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

Protected: Object Detection:Sliding Window Method and Negative Example Sequential Selection with Exampler-SVM, R-CNN

Various classifiers for object detection (Sliding Window Method and Negative Example Sequential Selection and Exampler-SVM, R-CNN) for digital transformation and artificial intelligence tasks.

2021.09.26

推論技術:inference Technology検索技術:Search Technology機械学習:Machine Learning深層学習:Deep Learning画像認識技術