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Education ; NTIC AND Data mining

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58 Documents

LlamaIndex 🦙 sur X : "brand-new course on Building Agentic RAG with LlamaIndex with @DeepLearningAI + @AndrewYNg..."

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2024-05-09 About

ColBERT Inference in the Browser

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2024-03-08 About

Announcing Vespa Long-Context ColBERT | Vespa Blog

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2024-03-03 About

[2307.15936] A Theory for Emergence of Complex Skills in Language Models

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2024-02-24 About

fast.ai - Can LLMs learn from a single example?

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2023-10-21 About

fast.ai - Mojo may be the biggest programming language advance in decades

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2023-05-06 About

Daniel Vila Suero sur Twitter : "Data quality is key for LLMs, but we're building Open Source LLMs with data of "unknown" quality... Introducing Alpaca GarbageCollector..."

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2023-04-05 About

[2304.01982] Rethinking the Role of Token Retrieval in Multi-Vector Retrieval

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2023-04-05 About

[2203.14465] STaR: Bootstrapping Reasoning With Reasoning

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2023-02-07 About

Andrej Karpathy sur Twitter : "Let's build GPT: from scratch, in code, spelled out."

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2023-01-28 About

Neural Networks: Zero To Hero

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2023-01-28 About

Self-Attention - Transformer Network | Coursera

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2022-09-11 About

[2006.05987] Revisiting Few-sample BERT Fine-tuning

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2022-03-21 About

Document Matching for Job Descriptions | Semantic Scholar (2021)

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2022-03-09 About

[2112.09118] Towards Unsupervised Dense Information Retrieval with Contrastive Learning

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2021-12-21 About

A Moderate Proposal for Radically Better AI-powered Web Search

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2021-07-10 About

fastai v2 cheat sheets

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2021-05-10 About

exBERT: Extending Pre-trained Models with Domain-specific Vocabulary Under Constrained Training Resources - ACL Anthology

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**Focus on the Embedding of Domain-specific Vocabulary.**

> exBERT
adds a new domain-specific vocabulary and the corresponding
embedding layer, as well as a small
extension module to the original unmodified model

> a pretraining
method allowing **low-cost embedding of
domain-specific vocabulary in the context of an
existing large pre-trained model such as BERT**

> exBERT... explicitly incorporates
the new domain’s vocabulary, while being able to
**reuse the original pre-trained model’s weights as is**
to reduce required computation and training data. Specifically, exBERT extends BERT by augmenting
its embeddings for the original vocabulary with
new embeddings for the domain-specific vocabulary
via **a learned small “extension” module**. **The
output of the original and extension modules are
combined via a trainable weighted sum operation**

In a way similar to concept developed in

> [[1902.00751] Parameter-Efficient Transfer Learning for NLP](doc:2021/04/1902_00751_parameter_efficien), but not in the fine-tuning paradigm.

[Github](https://github.com/cgmhaicenter/exBERT)

2021-04-11 About

[2012.04584] Distilling Knowledge from Reader to Retriever for Question Answering

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> a method to train an information retrieval module for downstream tasks, **without using pairs of queries and documents as annotations**.

Uses two models (standard pipeline for open-domain QA):

- the first one retrieves documents from a large source of knowledge (the retriever)
- the second one processes the support documents to solve the task (the reader).

> First the retriever selects support passages in a large knowledge
source. Then these passages are processed by the reader, along with the question, to generate an
answer

Inspired by knowledge distillation: the reader model is the teacher and the retriever is the student.

> More precisely, we use a sequence-to-sequence model as the reader, and use
the attention activations over the input documents as synthetic labels to train the retriever. 
> (**train the retriever by learning to approximate the attention score of the reader**)

Refers to:

- [REALM: Retrieval-Augmented Language Model Pre-Training](doc:2020/12/2002_08909_realm_retrieval_a)
- [Dehghani: Neural Ranking Models with Weak Supervision](doc:?uri=https%3A%2F%2Farxiv.org%2Fabs%2F1704.08803)

2020-12-11 About

Should you use FastAI? - deeplearningbrasilia - Medium

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fast.ai

2020-04-27 About

BERT, ELMo, & GPT-2: How Contextual are Contextualized Word Representations? | SAIL Blog

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2020-03-28 About

CS294-158-SP20 Deep Unsupervised Learning Spring 2020

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2020-03-08 About

fastai/fastpages: An easy to use blogging platform, with enhanced support for Jupyter Notebooks.

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2020-02-25 About

FastHugs | ntentional

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2020-02-19 About

[2002.04688] fastai: A Layered API for Deep Learning

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2020-02-13 About

Jeremy Howard sur Twitter : "The fastai paper (with @GuggerSylvain) covers v2..."

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2020-02-13 About

Your own blog with GitHub Pages and fast_template (4 part tutorial) · fast.ai

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2020-01-21 About

Syncing your blog with your PC, and using your word processor · fast.ai

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2020-01-19 About

fastai/nbdev: Create delightful python projects using Jupyter Notebooks

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2020-01-12 About

Lecture 14 – Contextual Vectors | Stanford CS224U: Natural Language Understanding | Spring 2019

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2020-01-05 About

[1911.00172] Generalization through Memorization: Nearest Neighbor Language Models

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2019-12-20 About

Fastai with Transformers (BERT, RoBERTa, XLNet, XLM, DistilBERT)

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2019-11-30 About

Bayesian deep learning with Fastai : how not to be uncertain about your uncertainty !

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2019-11-29 About

Finding Data Block Nirvana (a journey through the fastai data block API) — Part 2

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2019-11-01 About

Efficient multi-lingual language model fine-tuning · fast.ai NLP

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2019-10-22 About

[1802.07044] The Description Length of Deep Learning Models

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2019-10-11 About

Rick Wierenga's blog posts about fast.ai

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Fast.ai course

2019-08-12 About

Lesson 3 - Self Driving Cars

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2019-08-05 About

course-nlp/2-svd-nmf-topic-modeling.ipynb at master · fastai/course-nlp

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2019-07-11 About

new fast.ai course: A Code-First Introduction to Natural Language Processing · fast.ai

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2019-07-09 About

Introducing FastBert — A simple Deep Learning library for BERT Models

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2019-05-23 About

Radek Osmulski sur Twitter : "You would expect a difference in row access times depending on the type of a sparse matrix, but I didn't realize the difference would be so big!

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2019-05-05 About

GCP and Fast Ai v1: A full setup that’ll work – mc.ai

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2019-05-03 About

Contrastive Unsupervised Learning of Semantic Representations: A Theoretical Framework – Off the convex path (2019-03)

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2019-03-20 About

fast.ai Embracing Swift for Deep Learning · fast.ai

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2019-03-07 About

Finding Data Block Nirvana (a journey through the fastai data block API)

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fast.ai

2019-01-15 About

DeepLearning Images Revision M13/14. PyTorch 1.0. Git Integration. Smaller Boot Time.

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2018-12-12 About

GCP | fast.ai course v3

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2018-12-05 About

Fast.ai with Google Colab

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2018-12-02 About

Tutorial on Text Classification (NLP) using ULMFiT and fastai Library in Python - Analytics Vidhya

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2018-12-01 About

Notes from Coursera Deep Learning courses by Andrew Ng

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2018-03-05 About

fast.ai · Making neural nets uncool again

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fast.ai

2017-11-28 About

An overview of word embeddings and their connection to distributional semantic models - AYLIEN (2016)

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2017-07-20 About

Don’t count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors (2014)

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2017-05-18 About

How is GloVe different from word2vec? - Quora

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2017-05-18 About

R Programming | Coursera

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Coursera: R Programming

2015-01-06 About

Mining of Massive Datasets

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2014-08-29 About

Showing distribution of Open University course topics with R and SPARQL « LinkedUp DevTalk

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2013-05-08 About