Machine Learning & Artificial Intelligence

Today, we’re releasing our LLaMA (Large Language Model Meta AI) foundational model with a gated release. LLaMA is more efficient and competitive with previously published models of a similar size on existing benchmarks.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

PaLM 2 - Google’s next generation large language model.

LaMDA adds pieces to one of the most tantalizing sections of the language puzzle: conversation.

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A large language model (LLM) is a type of artificial intelligence model that has been trained to recognize and generate vast quantities of written human language.

Nature Biotechnology - Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene...

A neural network is a series of algorithms that seek to identify relationships in a data set via a process that mimics how the human brain works.

Artificial Intelligence Neural Networks - Yet another research area in AI, neural networks, is inspired from the natural neural network of human nervous system.

This definition explains the meaning of Artificial Neural Network and why it matters.

This definition explains what an Artificial Neural Network (ANN) is and how they learn and operate. Various types of ANN computational models are listed and described as well as the applications, a...

“Deep learning,” the machine-learning technique behind the best-performing artificial-intelligence systems of the past decade, is really a revival of the 70-year-old concept of neural networks.

Artificial Neural Network Tutorial with Introduction, History of Artificial Neural Network, What is ANN, Adaptive Resonance Theory, Building Blocks, Genetic Algorithm etc.

A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions.

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The Artificial Neural Network (ANN) is a deep learning method that arose from the concept of the human brain Biological Neural Networks.

Find out what a neural network is, how and why businesses use neural networks,, and how to use neural networks on AWS.

Learn about neural networks that allow programs to recognize patterns and solve common problems in artificial intelligence, machine learning and deep learning.

Vector is a list of numbers. Vector is widely used in the machine learning area as it is a foundation for many ML methods, like supervised…

A vector is a data structure with at least two components, as opposed to a scalar, which has just one. For example, a vector can represent velocity, an idea that combines speed and direction: wind velocity = (50mph, 35 degrees North East). A scalar, on the other hand, can represent something with one value like temperature or height: 50 degrees Celsius, 180 centimeters. Therefore, we can represent two-dimensional vectors as arrows on an x-y graph, with the coordinates x and y each representing one of the vector’s values.

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Naive Bayes Algorithm is a classification method that uses Bayes Theory. It assumes the presence of a specific attribute in a class.

Sklearn Naive Bayes Classifier Python. Learn how to build & evaluate a Gaussian Naive Bayes Classifier using Python's Scikit-learn package.

The Naive Bayes classifier works on the principle of conditional probability. Understand where the Naive Bayes fits in the machine learning hierarchy. Read on!

Learn how Naïve Bayes classifiers uses principles of probability to perform classification tasks, like topic classification.

Naive Bayes is the most popular machine learning classification method. Understand Naive Bayes classifier with different applications and examples.

Naive Bayes methods are a set of supervised learning algorithms based on applying Bayes’ theorem with the “naive” assumption of conditional independence between every pair of features given the val...