IMU (Inertial Measurement Unit) is one of the common sensor to provide motion data in a time-series format. In this post we review it.

Introduction

Where can we find an IMU sensor?

Actually, almost everywhere! Let’s start with our smartphones. Most smartphone devices are equipped with an IMU sensor inside, a MEMS (Micro-electromechanical Systems) technology. It is also placed in many Tablet devices. …


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.

Image by Author

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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I first came across the Kalman filter during my undergraduate studies when I took the navigation systems class. It was the last lecture, and the professor said it is out of the course syllabus, but if someone will deal with real-time applications, he is expected to meet it again. He was right, and I kept studying for a master’s degree in the field of Guidance, Control, and Navigation (GCN) at the Aerospace Engineering Faculty of the Technion. I came across the Kalman filter again, where I used it to filter noisy measurements from various sensors during real-time navigation problems. Later…


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

https://www.researchgate.net/publication/345435009_Length_Learning_for_Planar_Euclidean_Curves

In this current work, we address a fundamental question in the field of geometry where we aim to reconstruct a basic property using DNN. The simplest geometric object…


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)

The confusion matrix summarizes the performance of a supervised learning algorithm in ML. It is more…


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

Barak Or

Founder @ ALMA, PhD Candidate, AI Researcher.

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