Deep Reinforcement learning has been a rising field in the last few years. A good approach to start with is the value-based method, where the state (or state-action) values are learned. In this post, a comprehensive review is provided where we focus on Q-learning and its extensions.

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A Short Introduction to Reinforcement Learning (RL)


Machine Learning

The random forest model is considered one of the promising ML ensemble models that recently became highly popular. In this post, we review the last trends of the random forest.

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Ensemble Models-Intro

Random Forest-Background


The Kalman filter is one of the most influential ideas used in Engineering, Economics, and Computer Science for real-time applications. This year we mention 60 years for the novel publication. This post is the first one in the series of “Kalman filter celebrates 60”.

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Getting Started

A fundamental problem in geometry was solved using a Deep Neural Network (DNN). We learned a geometric property from examples in the supervised learning approach. As the simplest geometric object is a curve, we focused on learning the length of planar curves. For this reason, the fundamental length axioms were reconstructed and the ArcLengthNet was established.

Introduction


It is very common to use the F1 measure for binary classification. This is known as the Harmonic Mean. However, a more generic F_beta score criterion might better evaluate model performance. So, what about F2, F3, and F_beta? In this post, we will review the F measures.

Intro

Preliminary: Confusion matrix, Precision, and Recall

Confusion matrix (Image by author)


Intro


COVID-19 has affected the worldwide economy, politics, education, tourism, and actually EVERYTHING. Many academic papers address trends prediction in various fields due to COVID-19, with the power of Artificial Intelligence.

Background

Google COVID-19


Hands-on Tutorials

In this post, we deal with exploding and Vanishing Gradient in Time Series and in particular in Recurrent Neural Network (RNN) by Truncated BackPropagation Through Time and Gradient Clipping.

Intro


On October 5 2020 Python releases its 3.9 version. In this post, we review several amazing features and point out the relevant sources for further reading.

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Introduction


The reinforcement learning field is used in many robotics problems and has a unique mechanism, where rewards should be accumulated through actions. But, what about the time between these actions?

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What is the role of the discount factor in RL?

Barak Or

Founder @ ALMA, PhD Candidate, AI Researcher.

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