Rasa Algorithm Whiteboard - Understanding Word Embeddings 1: Just Letters
We're making a few videos that highlight word embeddings. Before training word embeddings we figured it might help the intuition if we first trained some letter embeddings. It might suprise you but the idea with an embedding can also be demonstrated with letters as opposed to words. We're
From playlist Algorithm Whiteboard
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
Symplectic embeddings, integrable systems and billiards - Vinicius Ramos
Symplectic Dynamics/Geometry Seminar Topic: Symplectic embeddings, integrable systems and billiards Speaker: Vinicius Ramos Affiliation: Member, School of Mathematics Date: January 27, 2020 For more video please visit http://video.ias.edu
From playlist Mathematics
EMBERCONF 2015 - THE ART OF EMBER DEPLOYMENT
BY: LUKE MELIA My team and I decided to invest in making our deployments awesome. When I told people about our approach, the community responded with excitement and new OSS implementations. This talk will show you how to make your team’s deployments delightful and empowering instead of s
From playlist EmberConf 2015
Jasna Urbančič (11/03/21):Optimizing Embedding using Persistence
Title: Optimizing Embedding using Persistence Abstract: We look to optimize Takens-type embeddings of a time series using persistent (co)homology. Such an embedding carries information about the topology and geometry of the dynamics of the time series. Assuming that the input time series
From playlist AATRN 2021
EmberConf 2014 HTMLBars: The Next-Generation of Templating in Ember.js by Erik Bryn and Kris Selden
The Ember.js community is ablaze with excitement over HTMLBars. Not only will it give us great syntax in our templates, but it will also usher in next-generation rendering performance in an upcoming 1.x stable release. Erik and Kris will walk through the design decisions and usage examples
From playlist EmberConf 2014
EmberConf 2019 - Intro to Ember Editions & Octane by Robert Jackson
Intro to Ember Editions & Octane by Robert Jackson
From playlist EmberConf 2019
Sketching and embedding are equivalent for norms - Alex Andoni
Computer Science/Discrete Mathematics Seminar II Topic: Sketching and embedding are equivalent for norms Speaker: Alex Andoni Affiliation: Columbia University Date: January 31, 2017 For more video, visit http://video.ias.edu
From playlist Mathematics
ELMo (Deep contextualized word representations)
I summarized and visualized ELMo in this short video. ELMo provides contextualized word embedding which provides dynamic embedding depends on context while Wordvec, or Glove only gives fixed embedding.
From playlist 텐서플로2 딥러닝
Supercharging Semantic Search with Pinecone and Cohere
Building your semantic search applications doesn’t have to be tedious and painful; Cohere and Pinecone are teaming up to show you how. Through an interactive demo, you will learn how to use Pinecone and Cohere to create sentence embeddings, index them in a vector database, and then identif
From playlist Talks
Beyond Semantic Search with OpenAI and Pinecone
An interactive and practical workshop on building AI-powered semantic applications on top of OpenAI and Pinecone. We will do an end-to-end tutorial on building semantic search, text summarization, question-answering, entity extraction, and other applications. No ML expertise is needed: If
From playlist Talks
RubyConf 2017: make mruby more portable: Why and How by Yurie Yamane & Masayoshi Takahashi
make mruby more portable: Why and How by Yurie Yamane & Masayoshi Takahashi Physical computing is very fascinating and fun, but there are also difficulties that were not found in normal Ruby programming. One of the issues is its low portability. Unlike PC, some computer boards that direct
From playlist RubyConf 2017
Getting Started: Semantic Search at Scale
Learn how to build your first semantic search application. In this workshop, you will learn what semantic search is and how to build an application that leverages it, without needing extensive ML experience. You will learn about different semantic search applications, and how to use Pineco
From playlist Talks
Kaggle Live-Coding: Making text sound old-timey with transformers (Python)! | Kaggle
Join Kaggle data scientist Rachael live as she works on data science projects! This week we're going to start on a project to make current English sound a little more like early Modern English (think Shakespeare) with transformers. SUBSCRIBE: http://www.youtube.com/user/kaggledotcom?sub_c
From playlist Kaggle Live Coding | Kaggle
Searching Freely: Using GPL for Semantic Search ft. Nils Reimers
We’re excited to host Nils Reimers, creator of SBERT and researcher at HuggingFace, to talk about the latest advances in semantic search. This time, he’ll be demonstrating the power of training sentence transformer models using Generative Pseudo-Labeling (GPL), and how this can enable sema
From playlist Talks
RustConf 2018 - Getting Something for Nothing by James Munns
RustConf 2018 - Getting Something for Nothing by James Munns This talk explores how to use the Rust Type System and Borrow Checker to write safe abstractions of hardware, even when using direct control of memory mapped peripherals with unsafe blocks. Because these techniques move all (or
From playlist RustConf 2018
Alan Sola: Clark measures for rational inner functions
HYBRID EVENT Recorded during the meeting "Frontiers of Operator Theory" the November 30, 2021 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathematicians on CIRM's Audiovis
From playlist Analysis and its Applications
Rasa Community Showcase: Assistant Highlights & Interview with Superhero Julian Gerhard
In our first edition, we will take a look at 5 assistants made with Rasa Open Source and chat to Julian Gerhard about his contribution to byte pair embeddings! ----- Learn more about Rasa: https://rasa.com Rasa documentation: http://rasa.com/docs Join the Rasa Community: https://forum.ra
From playlist Community Showcase
Understanding the Origins of Bias in Word Embeddings
Toronto Deep Learning Series Author Speaking For more details, visit https://tdls.a-i.science/events/2019-03-18/ Speaker: Marc Etienne Brunet (author) Facilitator: Waseem Gharbieh Abstract: The power of machine learning systems not only promises great technical progress, but risks soc
From playlist Natural Language Processing