article thumbnail

A Friendly Introduction to Support Vector Machines

KDnuggets

This article explains the Support Vector Machines (SVM) algorithm in an easy way.

article thumbnail

Coding Random Forests in 100 lines of code*

KDnuggets

There are dozens of machine learning algorithms out there. It is impossible to learn all their mechanics; however, many algorithms sprout from the most established algorithms, e.g. ordinary least squares, gradient boosting, support vector machines, tree-based algorithms and neural networks.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

A Non-Deep Learning Approach to Computer Vision

Heartbeat

Scale-Invariant Feature Transform (SIFT) This is an algorithm created by David Lowe in 1999. It’s a general algorithm that is known as a feature descriptor. After picking the set of images you desire to use, the algorithm will detect the keypoints of the images and store them in a database. It detects corners.

article thumbnail

A comprehensive guide to learning LLMs (Foundational Models)

Mlearning.ai

YouTube Introduction to Sequence Learning and Attention Mechanisms Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 8 — Translation, Seq2Seq, Attention — YouTube Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 7 — Translation, Seq2Seq, Attention — YouTube 2.

article thumbnail

Computer Vision and Deep Learning for Healthcare

PyImageSearch

Machine learning algorithms can also recognize patterns in DNA sequences and predict a patient’s probability of developing an illness. These algorithms can design potential drug therapies, identify genetic causes of disease, and help understand the mechanisms underlying gene expression.

article thumbnail

Best Machine Learning Datasets

Flipboard

Importance and Role of Datasets in Machine Learning Data is king. Algorithms are important and require expert knowledge to develop and refine, but they would be useless without data. Datasets are to machine learning what fuel is to a car: they power the entire process.

article thumbnail

How HSR.health is limiting risks of disease spillover from animals to humans using Amazon SageMaker geospatial capabilities

AWS Machine Learning Blog

According to health organizations such as the Centers for Disease Control and Prevention ( CDC ) and the World Health Organization ( WHO ), a spillover event at a wet market in Wuhan, China most likely caused the coronavirus disease 2019 (COVID-19). One of the models used is a support vector machine (SVM). min()) * 100).round(2)

ML 79