Co-occurrence network, sometimes referred to as a semantic network, is a method to analyze text that includes a graphic visualization of potential relationships between people, organizations, concepts, biological organisms like bacteria or other entities represented within written material. The generation and visualization of co-occurrence networks has become practical with the advent of electronically stored text compliant to text mining. By way of definition, co-occurrence networks are the collective interconnection of terms based on their paired presence within a specified unit of text. Networks are generated by connecting pairs of terms using a set of criteria defining co-occurrence. For example, terms A and B may be said to “co-occur” if they both appear in a particular article. Another article may contain terms B and C. Linking A to B and B to C creates a co-occurrence network of these three terms. Rules to define co-occurrence within a text corpus can be set according to desired criteria. For example, a more stringent criteria for co-occurrence may require a pair of terms to appear in the same sentence. Co-occurrence networks were found to be particularly useful to analyze large text and big data, when identifying the main themes and topics (such as in a large number of social media posts), revealing biases in the text (such as biases in news coverage), or even mapping an entire research field. (Wikipedia).
From playlist Week 9: Social Networks
If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist Networking
Covariance (1 of 17) What is Covariance? in Relation to Variance and Correlation
Visit http://ilectureonline.com for more math and science lectures! To donate:a http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn the difference between the variance and the covariance. A variance (s^2) is a measure of how spread out the numbers of
From playlist COVARIANCE AND VARIANCE
What is a Coordinate Covalent Bond?
This chemistry video tutorial provides a basic introduction into coordinate covalent bond. Line any covalent bond, electrons are shared. However, in a coordinate covalent bond, one atom donates both electrons that contribute to the formation of the bond. A lewis acid lewis base reaction
From playlist New AP & General Chemistry Video Playlist
Word embeddings are one of the coolest things you can do with Machine Learning right now. Try the web app: https://embeddings.macheads101.com Word2vec paper: https://arxiv.org/abs/1301.3781 GloVe paper: https://nlp.stanford.edu/pubs/glove.pdf GloVe webpage: https://nlp.stanford.edu/proje
From playlist Machine Learning
Kaggle Live-Coding: Graphing entity co-occurrence in online rumors (part 3) | Kaggle
Join Kaggle data scientist Rachael live as she works on data science projects! See all previous livestreams here: https://www.youtube.com/watch?v=i92VI289zWw&list=PLqFaTIg4myu9f21aM1POYVeoaHbFf1hMc SUBSCRIBE: http://www.youtube.com/user/kaggledotcom?sub_confirmation=1&utm_medium=youtube&
From playlist Kaggle Live Coding | Kaggle
Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 2 - Neural Classifiers
For more information about Stanford's Artificial Intelligence professional and graduate programs visit: https://stanford.io/2ZB72nu Lecture 2: Word Vectors, Word Senses, and Neural Network Classifiers 1. Course organization (2 mins) 2. Finish looking at word vectors and word2vec (13 mins)
From playlist Stanford CS224N: Natural Language Processing with Deep Learning | Winter 2021
Kaggle Live-Coding: Mapping the Data Science Package Ecosystem | Kaggle
Join Kaggle data scientist Rachael live as she works on data science projects! See all previous livestreams here: https://www.youtube.com/watch?v=JK9sOIUOysk&t=0s&list=PLqFaTIg4myu9f21aM1POYVeoaHbFf1hMc SUBSCRIBE: http://www.youtube.com/user/kaggledotcom?sub_confirmation=1&utm_medium=you
From playlist Kaggle Live Coding | Kaggle
Lecture 3 | GloVe: Global Vectors for Word Representation
Lecture 3 introduces the GloVe model for training word vectors. Then it extends our discussion of word vectors (interchangeably called word embeddings) by seeing how they can be evaluated intrinsically and extrinsically. As we proceed, we discuss the example of word analogies as an intrins
From playlist Lecture Collection | Natural Language Processing with Deep Learning (Winter 2017)
Star Network - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Kaggle Live-Coding: Graphing entity co-occurrence in online rumors | Kaggle
Join Kaggle data scientist Rachael live as she works on data science projects! See all previous livestreams here: https://www.youtube.com/watch?v=i92VI289zWw&list=PLqFaTIg4myu9f21aM1POYVeoaHbFf1hMc SUBSCRIBE: http://www.youtube.com/user/kaggledotcom?sub_confirmation=1&utm_medium=youtube&
From playlist Kaggle Live Coding | Kaggle
Kaggle Live-Coding: Named Entity Recognition | Kaggle
Join Kaggle data scientist Rachael live as she works on data science projects! See all previous live-coding streams here: https://www.youtube.com/watch?v=i92VI289zWw&list=PLqFaTIg4myu9f21aM1POYVeoaHbFf1hMc SUBSCRIBE: http://www.youtube.com/user/kaggledotcom?sub_confirmation=1&utm_medium=
From playlist Kaggle Live Coding | Kaggle
Lecture 4 – Word Vectors 3 | Stanford CS224U: Natural Language Understanding | Spring 2019
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai Professor Christopher Potts Professor of Linguistics and, by courtesy, Computer Science Director, Stanford Center for the Study of Language and Information http:
From playlist Stanford CS224U: Natural Language Understanding | Spring 2019
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From playlist Chemistry
Natural Language Processing (NLP) Approach to Automate Patients’ Testimonials Analysis
Install NLP Libraries https://www.johnsnowlabs.com/install/ Register for Healthcare NLP Summit 2023: https://www.nlpsummit.org/#register Watch all NLP Summit 2022 sessions: https://www.nlpsummit.org/nlp-summit-2022-watch-now/ Presented by Melissa Rollot, Manager Data Scientist at Quin
From playlist NLP Summit 2022
Watch more videos on http://www.brightstorm.com/science/chemistry SUBSCRIBE FOR All OUR VIDEOS! https://www.youtube.com/subscription_center?add_user=brightstorm2 VISIT BRIGHTSTORM.com FOR TONS OF VIDEO TUTORIALS AND OTHER FEATURES! http://www.brightstorm.com/ LET'S CONNECT! Facebook ► h
From playlist Chemistry
Modern NLP: First Surge of Deep NLP - Session 2, part 2
Vanishing and exploding gradient problem continued LSTM: architecture & equations Autoencoders: representation learning Seq2Seq models Word-to-Vec Heirarchical softmax Noise constrastive estimation GloVe
From playlist Modern Natural Language Processing (hands on)