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
ICT技術:ICT Technology
Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp Reading Memo
Explanation of basic ideas of various artificial intelligence techniques using LISP (GPS, ELIZA, SUDENT, symbol processing systems, natural language processing systems, Prolog, expert systems, etc.)
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.
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
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
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)
Comparison of tensorflow, Keras and pytorch
Comparison of tensorflow, keras, and pytorch, deep learning frameworks used for digital transformation and artificial intelligence tasks
Protected: Evolving Deep Learning with PyTorch(OpenPose, SSD, AnoGAN, Efficient GAN, DCGAN, Self-Attention GAN, BERT, Transformer, GAN, PSPNet, 3DCNN, ECO)
OpenPose, SSD, AnoGAN, Efficient GAN, DCGAN, Self-Attention GAN, BERT, Transformer, GAN using pytorch for Digital Transformation and Artificial Intelligence tasks, PSPNet,3DCNN,ECO and other advanced DNNs
Protected: Advanced deep learning with Python and Keras (1) Complex networks using the Keras Functional API
Construction of complex network models using Keras functional API with python/keras for digital transformation and artificial intelligence tasks (for multimodal problems, etc.)
Protected: DNNs for text and sequences with python and Keras (4) Sequence processing with bidirectional RNNs and CNNs
Bidirectional RNN and CNN application to sequence data in python/keras for digital transformation and artificial intelligencetasks.