Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

Both long-time franchise-lovers and curious new players will find themselves right at home in the Town-on-Gorkhon ...

This package is intended to make MATPOWER installable from PyPI. We did not change anything from MATPOWER package, instead, we used a copy of MATPOWER (currently Version 8.1) and wrapped it as python ...

Path Guide is a completely plug-and-play indoor navigation service that does not require maps or any additional equipment. Using Path Guide, users can create routes by recording sensory data with ...

Abstract: Modern multimode sub-6GHz receivers heavily employ current-mode passive mixers and N-path filters to simultaneously satisfy the noise requirements and deal with large in-band and out-of-band ...

Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Jupyter Notebook so that you can run and modify the code in your browser. What ...

Abstract: I welcome you to the fourth issue of the IEEE Communications Surveys and Tutorials in 2021. This issue includes 23 papers covering different aspects of communication networks. In particular, ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

Get the inside scoop on how colleges assess your high school and its course rigor. Featuring a former Admissions Officer, you'll gain crucial insights and actionable strategies during this 60-min ...