A technical blog

Besides traditional data-based methods on Machine Learning, e.g. Clustering or Maximum Likelihood Estimation, Reinforcement Learning is a family in which tiny (or even no) data is required to do the training and testing phase. In this post, I would give a minor introduction on Reinforcement Learning, its basic concepts and methods.

The needs for appropriate deep neural networks for most modern problems have increased dramatically, and finding the right architecture is a challenge. Almost deep architectures nowadays are manually designed with tremendous times of trial-and-errors and state-of-the-arts are those with multiple layers, connections ignoring a suitable explanation.

Data analysis on number of blood cells, which are white blood cells and red blood cells, per a certain blood volume could help us observe our medical situation. In this blog, we introduce a faster method to recognize disease via the number of leukocytes.

Data analysis on number of blood cells, which are white blood cells and red blood cells, per a certain blood volume could help us observe our medical situation. In this blog, we introduce a faster method to recognize disease via the number of leukocytes.

Introduce a deep learning approach to the problem of recognizing emotions in real time.

Propose a rapidly testing method which has a high productivity in a short time, which is to use Deep Convolutional Neural Network to detect COVID-19 on Chest X-ray (CXR) images to cope with the present pandemic.