artificial intelligence

C言語

Protected: A concrete algorithm for Markov chain Monte Carlo: Metropolis method (1)Overview

Overview of the Metropolis method in MCMC methods used for probability integration and other aspects of machine learning for digital transformation and artificial intelligence tasks.
C言語

Protected: General Theory of MCMC Methods: Applying Markov Chains to Monte Carlo Methods

Application of Markov Chains to Monte Carlo methods for efficient computation of probability/combination and other integrals for digital transformation and artificial intelligence tasks.
web技術:web technology

Chatbots: The Future Transformed by the Evolution of AI and Robotics – Reading Memo

Chatbot technology trends, business development and future prospects for use in digital transformation and artificial intelligence tasks
C言語

Protected: On probability, expectation and Monte Carlo methods

Explanation of the Monte Carlo method, which is the basis of the Markov Chain Monte Carlo (MCMC) method used in integral calculations for machine learning used in digital transformation and artificial intelligence tasks.
推論技術:inference Technology

Creating Logic, Part 3 – Another Look at Logic Reading Notes

Foundations of logic (deductive reasoning, syntax and semantics) in mathematical logic used for reasoning mechanisms in artificial intelligence tasks.
python

Protected: Generative Deep Learning with Python and Keras (1) Text generation using LSTM

Text-generating DNN using LSTM with python/keras for digital transformation and artificial intelligence tasks
python

Protected: Advanced deep learning with Python and Keras (3) Model optimization methods

Optimizing networks for deep learning with python/keras for digital transformation and artificial intelligence tasks
python

Protected: Advanced deep learning with Python and Keras (2) Model monitoring using Keras callbacks and TensorBord

Monitoring of networks in deep learning process using pyton/keras for digital transformation and artificial intelligence tasks (monitoring of models using Keras callbacks and TensorBord)
Symbolic Logic

Creating Logic, Part 2: Expanding Logic Reading Notes

Fundamentals of logic (predicate logic and tableau, PPL, IPL) in mathematical logic utilized for reasoning mechanisms in artificial intelligence tasks.
微分積分:Calculus

This is a good introduction to deep learning (Machine Learning Startup Series)Reading Notes

Overview of deep learning for digital transformation and artificial intelligence tasks, including machine learning, gradient descent, regularization, error back propagation, self-encoders, convolutional neural networks, recurrent neural networks, Boltzmann machines, and reinforcement learning.
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