ODSC - Open Data Science

APRIL 28, 2023

Introduction to SpaCy SpaCy is a python library designed to provide a “complete” NLP pipeline, including ingestion, tokenization, tagging, representation, and even classification. Looking at the changes we made to the spaCy configuration to leap forward roughly a decade in NLP development brings that point home.

Deep Learning 98

Deep Learning Deep Learning Data Science Natural Language Processing 98

Towards AI

JULY 20, 2023

Authors suggest that these models, that have kept their self-attention/feed forward layers frozen (without fine-tuning) can actually match the performance of a fully trained model trained on the downstream task. For example, was it fast or slow, differences across languages etc. vision, computing numbers etc.).

Deep Learning 81

Deep Learning Deep Learning Data Analysis Data Analysis 81

Smart Data Collective

JUNE 7, 2019

Data, for instance, has to be processed fast so that the companies can keep up to the changing business and market conditions in real time. Using sensors, RFID tags and other tools can help deal with the flow of data in near real time. With today’s technology, there’s an increasing demand for stream processing. Conclusion.

Big Data 81

Big Data Big Data Data Analysis Data Analysis 81

Hacker News

MARCH 25, 2022

In addition, the math that transformers use lends itself to parallel processing, so these models can run fast. Transformers use positional encoders to tag data elements coming in and out of the network. Attention units follow these tags, calculating a kind of algebraic map of how each element relates to the others.

Machine Learning 181

Machine Learning Machine Learning AI AI 181

Flipboard

DECEMBER 6, 2023

In today’s fast-paced and data-driven financial landscape, Investor Relations Officers (IROs) play a critical role in fostering communication between a company and its shareholders, analysts, and investors. The idea was to use the LLM to first generate a SQL statement from the user question, presented to the LLM in natural language.

SQL 130

SQL Database AWS Machine Learning 130

Hacker News

AUGUST 21, 2023

It's called asynchronously from the client without needing to post back the entire page and by design, it's super fast and super easy to use. That is all - only from the home page. Which is bad. And then, unsurprisingly in retrospect, it started to be abused so I had to put a rate limit on it.

Azure 94

Azure 94

AssemblyAI

JANUARY 23, 2023

Looking forward: What’s next for Conversational Intelligence AI? For teams that compile and analyze conversational data, Conversational Intelligence AI has a wealth of benefits. Companies can then rely on this partner’s internal AI research team to iterate based on new research developments and innovation.

AI 52

AI AI Natural Language Processing Machine Learning 52

Explosion

JANUARY 12, 2018

Highlights included: Developed new deep learning models for text classification, parsing, tagging, and NER with near state-of-the-art accuracy. Published 13 pre-trained statistical models for tagging, parsing and NER in 8 languages, and extended tokenization support to 26 languages in total. cython-blis ?

Machine Learning 52

Machine Learning Machine Learning Supervised Learning Python 52

AWS Machine Learning Blog

AUGUST 23, 2023

Amazon CodeWhisperer, with its transformative power to fast-track not just coding but secure coding, fits well into the narrative. Enabling developer skills to undergo a reboot Most developers must undergo at least 4 months of training before being tagged to projects. The accurate code generation makes the lift easy.

AWS 73

AWS AI AI Computer Science 73

Alation

APRIL 4, 2023

The modern data stack (MDS) has some incredible benefits, namely robust, fast, and scalable services in the cloud. Joint users can search, curate, tag, and flag lineage easily, accelerating productivity and accuracy. The Benefits and Challenges of the Modern Data Stack Why are such integrations needed?

DataOps 52

DataOps Data Engineering Data Engineer Data Engineering 52

Explosion

NOVEMBER 9, 2016

It shouldn’t matter whether you’re flagging abusive posts or tagging emails that propose meetings. For instance, it’s often useful to pass forward a sequence of part-of-speech tags, in addition to the word IDs. You can then learn tag embeddings, and concatenate the tag embedding to the word embedding.

Deep Learning 52

Deep Learning Deep Learning Natural Language Processing Machine Learning 52

Explosion

APRIL 1, 2017

Each example consists of a context and its correct tag, provided by a human annotator. The output of the function is the weights table, W , which can be used to predict a tag given the context. To keep the example simple, the context consists of only three pieces of evidence: the word being tagged, and its two immediate neighbours.

Supervised Learning 40

Supervised Learning Machine Learning Machine Learning Algorithm 40

Explosion

SEPTEMBER 17, 2013

There are a tonne of “best known techniques” for POS tagging, and you should ignore the others and just use Averaged Perceptron. You should use two tags of history, and features derived from the Brown word clusters distributed here. About 50% of the words can be tagged that way.

Python 40

Python Algorithm Natural Language Processing Supervised Learning 40

Mlearning.ai

MARCH 2, 2023

However, since each token (and the previous hidden state) is fed consecutively into the same neural network (also referred to as cell), a long chain of operations must be computed during forward pass, which also leads to long gradient computation chains during optimization, also called multi-step backpropagation.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Explosion

OCTOBER 1, 2019

This brings the core team up to four developers – so you can look forward to a lot more to come. With steady improvements to our automation systems and new team members joining spaCy, we look forward to adding more languages soon. replaces the PhraseMatcher with a more straight-forward trie-based algorithm. seconds) v2.2.0

Algorithm 59

Algorithm Natural Language Processing Python Data Science 59

Alation

DECEMBER 22, 2022

Now my pointy-eared sources tell me that Alation is fast becoming the one-stop shop for everyone setting off on this new data journey. The elf stewards, already immersed in the catalog, were now supercharging their work to document, tag, and curate the flood of new data products. The result?

DataOps 52

DataOps Data Governance Tableau Big Data 52

phData

OCTOBER 20, 2023

However, it does include metadata and tags that help to distinguish semantic elements and create hierarchies of fields and records. To define data in XML, you utilize markup symbols, called tags, which enable complex data encoding and facilitate the integration of information flows across various systems.

Big Data 52

Big Data Big Data Database Hadoop 52

AssemblyAI

SEPTEMBER 22, 2023

Still, these improvements appeared far from the fast-paced progress observed in the image and text domain. What’s undeniable is that, with foundational ideas from LLMs and text-to-image models being adapted to the audio modality , the latest AI music generators have shown a giant leap forward in the quality of their outputs.

AI 98

AI AI Machine Learning Machine Learning 98

Explosion

DECEMBER 17, 2013

split() >>> tags, heads = parser.parse(tokens) >>> heads [-1, 2, 0, 0, 3, 0, 7, 5, 7, 10, 8, 0, 13, 15, 15, 11] >>> for i, h in enumerate(heads): head = tokens[heads[h]] if h >= 1 else 'None'. Example usage parser = parser.Parser() tokens = "Set the volume to zero when I 'm in a meeting unless John 's school calls".split()

Python 45

Python Algorithm Natural Language Processing 45

ODSC - Open Data Science

FEBRUARY 14, 2023

Sometimes it says it can’t answer a question, which is a great step forward! Moving Forward with LLMs Finally, the latest warning about ChatGPT comes from OpenAI itself. Lastly, OpenAI has plans to embed cryptographic tags into ChatGPT’s output in order to watermark the generated text. Bigger does not always equal better.”

Database 124

Database AI AI Natural Language Processing 124

The MLOps Blog

DECEMBER 7, 2022

It may not seem like a real problem, but when you have to spend money to implement something in the cloud, spending as little as a dollar or two can make the cost of failing (and that’s a natural part of developing these solutions, to fail and iterate fast to get the best results) very steep. 3 The SQS queues were messy to maintain.

ML 52

ML ML AWS ETL 52

Hacker News

DECEMBER 3, 2023

The very next day I published a blog post about how I made it so fast to search through 154M records and thus began a now 185-post epic where I began detailing the minutiae of how I built this thing, the decisions I made about how to run it and commentary on all sorts of different breaches. 3 years ago, I did 100% of everything myself.

AWS 176

AWS 176

Explosion

JANUARY 29, 2023

we started using logits during inference, which resulted in speedups of 27% when using a tagging + parsing pipeline. Madeesh and Daniël have written a blog post about fast transformer inference using Metal Performance Shaders. With the community and the team continuing to grow, we look forward to making 2023 even better.

Python 59

Python Data Scientist Machine Learning Machine Learning 59

AWS Machine Learning Blog

NOVEMBER 22, 2023

Use the “Generative AI” tag as you are browsing the session catalog to find them. Innovation Talks – Learn about the latest cloud technology from AWS technology leaders and discover how these advancements can help you push your business forward. And although our track focuses on generative AI, many other tracks have related sessions.

AWS 105

AWS ML ML AI 105

AWS Machine Learning Blog

DECEMBER 14, 2023

It takes just a few seconds to set up a new Space with fast launch instances and less than 60 seconds to run a Space. Conclusion The advancements in SageMaker Studio, particularly with the new JupyterLab experience, mark a significant leap forward in ML development. Additionally, version 4.0

ML 94

ML ML AI AI 94

Hacker News

NOVEMBER 22, 2023

Together this provides the top two reasons for why someone would like to strip their executables: To really make the executable as small and fast as possible. Thus we can provide two versions of all executables: one stripped that is small and fast, and an unstripped version that contains all the debugging comforts.

AWS 88

AWS 88

Explosion

OCTOBER 15, 2017

If you needed to add a process that should run between tagging and parsing, you’d have to dig into spaCy’s internals. All of this is specific to each model, and defined in the model’s meta.json – for example, a Spanish NER model requires different weights, language data and pipeline components than an English parsing and tagging model.

Natural Language Processing 52

Natural Language Processing Python Deep Learning Deep Learning 52

Mlearning.ai

SEPTEMBER 4, 2023

1] API: API access is available for easy and fast development. 7] For industries with strict regulatory requirements, such as healthcare, finance, or defense, private instances, and business accounts can address this issue but have a hefty price tag. CA, NY, and MA).[1] Market factors: Such an adoption strategy depends on another.

AI 52

AI AI Azure Machine Learning 52

Alation

AUGUST 26, 2021

Search metadata: Supports tagging and keywords to help people find relevant data. Artificial Intelligence and Machine Learning (AI & ML) are forward-looking. Artificial Intelligence, too, is a fast-growing market, valued at $21 billion. Business Intelligence (BI) is explanatory and backward-looking.

Data Governance 64

Data Governance ML ML Artificial Intelligence 64

Hacker News

FEBRUARY 2, 2023

My filesystem from 1985 records that it was fast work. Because in optimizing for parallelism, its individual processors were quite simple, and weren’t set up to do fast (e.g. So was this kind of thing what I had to look forward to in a life in academia? But that wasn’t going to work well for the Connection Machine.

Machine Learning 130

Machine Learning Machine Learning Algorithm Analytics 130

Mlearning.ai

MAY 23, 2023

Also, TensorFlow has a fast compilation speed as compared to Keras and Torch (other famous deep learning libraries). There are three types of wrapper methods, they are: Forward Selection: Here, one feature is tested at a time and new features are added until a good fit is obtained. TensorFlow is a very famous library in deep learning.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52