Efficient Java Matrix Library (EJML) is a linear algebra library for manipulating real/complex/dense/sparse matrices. Its design goals are; 1) to be as computationally and memory efficient as possible for both small and large matrices, and 2) to be accessible to both novices and experts. These goals are accomplished by dynamically selecting the best algorithms to use at runtime, clean API, and multiple interfaces. EJML is free, written in 100% Java and has been released under an Apache v2.0 license. EJML has three distinct ways to interact with it: 1) Procedural, 2) SimpleMatrix, and 3) Equations. The procedural style provides all capabilities of EJML and almost complete control over matrix creation, speed, and specific algorithms. The SimpleMatrix style provides a simplified subset of the core capabilities in an easy to use flow-styled object-oriented API, inspired by JAMA. The Equations style provides a symbolic interface, similar in spirit to Matlab and other CAS, that provides a compact way of writing equations. (Wikipedia).
How to Quickly Create a Matrix in GeoGebra; How to Multiply 2 Matrices
Creating a matrix in GeoGebra is EASY. You need to use the LIST icons { }. In GeoGebra, a matrix is actually a sequence of lists within a single list. This video shows how.
From playlist Algebra 1: Dynamic Interactives!
How do we add matrices. A matrix is an abstract object that exists in its own right, and in this sense, it is similar to a natural number, or a complex number, or even a polynomial. Each element in a matrix has an address by way of the row in which it is and the column in which it is. Y
From playlist Introducing linear algebra
Java Tutorial for Beginners to Expert [Full Course - 2020]
This is the latest #Java Programming tutorial for beginners to expert. Along the way you will learn everything you need to know about java programming. Java is a general-purpose programming language that is class-based, object-oriented, and designed to have as few implementation dependenc
From playlist Programming
Get the Code Here: http://goo.gl/srwIf Welcome to my Java Hash Table tutorial. A Hash Table is a data structure offers fast insertion and searching capabilities. The negative is that they are limited in size because they are based on arrays. They are also hard to order. People get confus
From playlist Java Algorithms
Matrix Algebra Basics || Matrix Algebra for Beginners
In mathematics, a matrix is a rectangular array or table of numbers, symbols, or expressions, arranged in rows and columns. This course is about basics of matrix algebra. Website: https://geekslesson.com/ 0:00 Introduction 0:19 Vectors and Matrices 3:30 Identities and Transposes 5:59 Add
From playlist Algebra
Linear Algebra for Computer Scientists. 12. Introducing the Matrix
This computer science video is one of a series of lessons about linear algebra for computer scientists. This video introduces the concept of a matrix. A matrix is a rectangular or square, two dimensional array of numbers, symbols, or expressions. A matrix is also classed a second order
From playlist Linear Algebra for Computer Scientists
This video defines elementary matrices and then provides several examples of determining if a given matrix is an elementary matrix. Site: http://mathispower4u.com Blog: http://mathispower4u.wordpress.com
From playlist Augmented Matrices
Linear Algebra 1.3 Matrices and Matrix Operations
My notes are available at http://asherbroberts.com/ (so you can write along with me). Elementary Linear Algebra: Applications Version 12th Edition by Howard Anton, Chris Rorres, and Anton Kaul
From playlist Linear Algebra
Get the Code Here: http://goo.gl/Zuatn Subscribe to Me: http://bit.ly/2FWQZTx Welcome to my tutorial on the Binary Tree in Java. On average a tree is more efficient then other data structures if you need to perform many different types of operations. In this tutorial I'll show you what a
From playlist Java Algorithms
Machine Learning by Andrew Ng [Coursera] 0208 Basic operations 0209 Moving data 0210 Computing on data 0211 Plotting data 0212 For, while, if statements, and functions 0213 Working on and submitting programming exercises 0214 Vectorization
From playlist Machine Learning by Professor Andrew Ng
AI-ML Live - 2 | Artificial Intelligence with Python | Artificial Intelligence Tutorial | Edureka
🔥NIT Warangal Post Graduate Program in AI & Machine Learning with Edureka: https://www.edureka.co/nitw-ai-ml-pgp This Edureka video on "Artificial Intelligence With Python" will provide you with a comprehensive and detailed knowledge of Artificial Intelligence concepts with hands-on exampl
From playlist Edureka Live Classes 2020
eurucamp 2015 - Lightning Talks
From playlist eurucamp 2015
Ruby Conf 12 - Building Data Driven Products with Ruby by Ryan Weald
Big data and data science have become hot topics in the developer community during the past year. This talk will show how ruby is used to build real data driven products at scale. Data scientist Ryan Weald walks through the building of data driven products at Sharethrough, from explorator
From playlist Ruby Conference 2012
Advanced Data Mining Course Tutorial - Weka
In this course you will learn about #advanced #data #mining which will boost your data mining skill to the utmost level. ** Topics of this course ** Advanced Data Mining (1.1: Introduction) Advanced Data Mining (1.2: Linear regression with lags) Advanced Data Mining (1.3: timeseriesFo
From playlist Data Mining
Boost the Search using Apache Solr | Edureka
Watch Sample Recording : http://www.edureka.co/apache-solr?utm_source=youtube&utm_medium=webinar&utm_campaign=solr-23-04-15 Apache Solr based on the Lucene Library, is an open-source enterprise Grade search engine and platform used to provide f
From playlist Webinars by Edureka!
Scaling Ruby with Actors, or How I Learned to Stop Worrying and Love Threads by Mike Perham
The last two years have been a personal tour of EventMachine, Fibers and Threads for me as I've toured the ecosystem looking for a developer-friendly, efficient solution for scaling Ruby. Historically Threads have performed poorly in Ruby but guess what? - recent events may change your min
From playlist Ruby Conference 2011
O'Reilly Webcast Computational Thinking Just Enough Math
The webcast introduces advanced math for business people — "just enough" to take advantage of open source frameworks — including graph theory, abstract algebra, optimization, bayesian statistics, and more advanced areas of linear algebra. These are needed for supply chain optimization, pri
From playlist O'Reilly Webcasts 3
Deep Learning Frameworks 2019 | Which Deep Learning Framework To Use | Deep Learning | Simplilearn
This Deep Learning tutorial covers all the essential Deep Learning frameworks that are necessary to build AI models. In this video, you will learn about the development of essential frameworks such as TensorFlow, Keras, PyTorch, Theano, etc. You will also understand the programming languag
From playlist Deep Learning Tutorial Videos 🔥[2022 Updated] | Simplilearn
Understanding Matrices and Matrix Notation
In order to do linear algebra, we will have to know how to use matrices. So what's a matrix? It's just an array of numbers listed in a grid of particular dimensions that can represent the coefficients and constants from a system of linear equations. They're fun, I promise! Let's just start
From playlist Mathematics (All Of It)
Unleashing the Power of BLOOM 176B with AWS ml.p4de.24xlarge, DJL & DeepSpeed: The Ultimate Boost!
More Power! How and where to run inference of an LLM w/ 176 billion parameter? Well, what about the most expensive ML instance on AWS? The most performant implementation for LLMs (utilizing latest .. and most expensive .. cloud infrastructure)? Some implementation ideas ... Regarding LLM
From playlist Large Language Models - ChatGPT, GPT-4, BioGPT and BLOOM LLM explained and working code examples