Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes. (⭐ 33906)
**ISLP book, I finished the first 2 chapters, but this book is not easy, and I want some guys to study this book together. Any tips to study this book?**...
Whether you need a wheeled machine or a mini, midi, large crawler or specialty, CASE excavators boast big power, intelligent hydraulics and unmatched reliability.
The training covers introduction to Julia, vector and array operations in Julia, followed by introductory machine learning techniques and applications. The course then takes a deep dive into introducing …
Kata Containers version 1.x agent (for version 2.x see https://github.com/kata-containers/kata-containers). Virtual Machine agent for hardware virtualized containers (⭐ 243)
Machine-readable representations of privacy policies are door openers for a broad variety of novel privacy-enhancing and, in particular, transparency-enhancing technologies (TETs). In order to generate such representations, transparency information n...
Style, March 26, 2018; Price, Scarlett. "Maddie Ziegler Stars In Tiffany & Co. Jewelry Campaign Video" Archived August 4, 2018, at the Wayback Machine
The concept of updating (or conditioning or revising) a probability distribution is fundamental in (machine) learning and in predictive coding theory. The two main approaches for doing so are called Pearl's rule and Jeffrey's rule. Here we make, for...
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Are you looking for a great price on a copier machine for sale or lease in Fairlawn, Ohio? Copy Machines Direct makes it easier than ever to compare prices on copiers in Ohio, which means you …
Post-election audits use the discrepancy between machine counts and a hand tally of votes in a random sample of precincts to infer whether error affected the electoral outcome. The maximum relative overstatement of pairwise margins (MRO) quantifies...
A guide to setting up a production-like Kubernetes cluster on a local machine (⭐ 971)
The worlds of Data Science (including big and/or federated data, machine learning, etc) and Astrophysics started merging almost two decades ago. For instance, around 2005, international initiatives such as the Virtual Observatory framework rose to st...
We consider the supervised learning problem of learning the price of an option or the implied volatility given appropriate input data (model parameters) and corresponding output data (option prices or implied volatilities). The majority of articles i...
Live wild fire data visualization, historical data analysis, future fires prediction based on Machine Learning model (⭐ 9)
Exploratory analysis of wild-fires in Australia & a machine learning approach for wildfire modeling in Google Earth Engine (⭐ 19)
Feb 7, 2017 · On the other hand, from statistical points (probabilistic approach) of view, we may emphasize more on generative models. For example, mixture of Gaussian Model, Bayesian Network, …
In the oil industry, undesirable events in oil wells can cause economic losses, environmental accidents, and human casualties. Solutions based on Artificial Intelligence and Machine Learning for Early Detection of such events have proven valuable for...
Oil and gas reserves are vital resources for the global economy, serving as key components in transportation, energy production, and industrial processes. However, oil and gas extraction and production operations may encounter several challenges, suc...
Training machine learning models for predicting stock market share prices is an active area of research since the automatization of trading such papers was available in real time. While most of the work in this field of research is done by training N...