AWS Machine Learning Blog

APRIL 7, 2023

Next, using an AWS Cloud9 environment or interactive development environment (IDE) of choice, download the requisite SageMaker packages and Docker Compose , a key dependency of JumpStart. infer-tensorflow-tc-bert-en-uncased-L-12-H-768-A-12-2.tar.gz Run the train_model.py amazonaws.com/tensorflow-inference:2.8-cpu sourcedir.tar.gz

AWS 80

AWS Clustering ML ML 80

Kaggle

JULY 23, 2020

This last step was rather critical here, since the CORD-19 dataset contains highly technical papers with scientific language that can’t be processed successfully by standard packages.

Data Science 63

Data Science Machine Learning Machine Learning Data Preparation 63

Explosion

JANUARY 29, 2023

With this add-on package, Thinc uses Apple’s Accelerate framework for matrix multiplication. It now handles training, packaging and deployment in a spaCy project structure that is easy to maintain and update in the future. Pipeline Device January 2022 (words/s) January 2023 (words/s) Delta Convolution CPU 25,421 25,573 +0.6%

Python 59

Python Data Scientist Machine Learning Machine Learning 59

Data Science Blog

NOVEMBER 8, 2022

Therefore we create a script package, register the scripts and run # them all in here return f"Hello {data['name']}" return "Hello World" if __name__ == '__main__': """ Creating a very basic debug app. Flask selbst ist ein sogenanntes Micro Framework und kann flexibel eingesetzt werden, für mehr Informationen empfiehlt sich z.b.

Python 130

Python Data Science Cloud Data 130

Explosion

OCTOBER 1, 2019

In addition to new model packages and features for training, evaluation and serialization, we’ve made lots of bug fixes, improved debugging and error handling, and greatly reduced the size of the library on disk. Version 2.2 of the spaCy Natural Language Processing library is leaner, cleaner and even more user-friendly.

Algorithm 59

Algorithm Natural Language Processing Python Data Science 59

How to Learn Machine Learning

JANUARY 21, 2023

La entrada Artificial Intelligence trends in 2023 se publicó primero en How to Learn Machine Learning. As always, thank you very much for reading How to Learn Machine learning , and have a great day!

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

Towards AI

AUGUST 16, 2023

There is no standard way to package and deploy models. An MLOps tool allows you to train, reuse, and deploy models with any library and package them into reproducible steps that other data scientists can use as a “black box” without needing to know which libraries you are using.

Machine Learning 94

Machine Learning Machine Learning ML ML 94

Explosion

NOVEMBER 16, 2021

paths] train = "path/to/train.spacy" dev = "path/to/dev.spacy" [nlp] lang = "en" pipeline = [] batch_size = 5000 We can generate a full configuration from this file using the fill-config command When running spacy train , you should still pass the complete config. Training is but one part of the experiment lifecycle.

Machine Learning 52

Machine Learning Machine Learning Python Data Preparation 52

Heartbeat

DECEMBER 27, 2023

Containers : Containers take an alternative approach, as they package just the application alongside its binaries, libraries, and dependencies and ship it all out as one package. So, you are sharing your entire development environment rather than sharing packaged dependencies and source code. Flask==2.1.2 gunicorn==20.1.0

Machine Learning 52

Machine Learning Machine Learning Python ML 52

AWS Machine Learning Blog

APRIL 17, 2023

client("comprehend") response = comprehend.detect_entities(LanguageCode = 'en', Text = df['name'].iloc[0]) In the following Data Wrangler flow, different functions from Python packages, NumPy, and SciPy are applied on the Titanic dataset as multiple steps. Choose Python (Pandas).

AWS 83

AWS ML ML Python 83

Precisely

FEBRUARY 5, 2024

That’s why the master data team at Pactiv , the world’s largest manufacturer and distributor of food packaging and foodservice products, needed help: even small design alterations for individual retailers required a new product creation request (PCR). Creating a new material master for this was tedious. The results?

Data Quality 59

Data Quality Analytics Analytics Database 59

AWS Machine Learning Blog

SEPTEMBER 8, 2023

These models have been packaged to be securely and easily deployable via Amazon SageMaker APIs. The new SageMaker JumpStart Foundation Hub allows you to easily deploy large language models (LLM) and integrate them with your applications.

K-nearest Neighbors 96

K-nearest Neighbors AWS ML ML 96

Explosion

MARCH 17, 2019

To use the pretrained weights, we can simply pass them as an argument to spacy train : python -m spacy train en /models/ /corpora/PTB_SD_3_3_0/train.gold.json /corpora/PTB_SD_3_3_0/dev.gold.json --n-examples 100 --pipeline parser --init-tok2vec pretrain-nv-model999.bin

Python 52

Python Natural Language Processing Deep Learning Deep Learning 52

Hacker News

SEPTEMBER 5, 2023

“This was accomplished by targeting the DevOps engineer’s home computer and exploiting a vulnerable third-party media software package, which enabled remote code execution capability and allowed the threat actor to implant keylogger malware,” LastPass officials wrote.

Computer Science 182

Computer Science Computer Science Analytics Analytics 182

Explosion

DECEMBER 14, 2021

nlp] lang = "en" pipeline = ["sentencizer","tok2vec","ner"] [components.tok2vec] source = ${paths.ner_model} component = "tok2vec" [components.ner] source = ${paths.ner_model} component = "ner" For the Benepar to work, we add an additional sentencizer component that creates sentence boundaries. [nlp] ✨ Our custom_code.py

Clustering 52

Clustering Machine Learning Machine Learning Natural Language Processing 52

Explosion

JANUARY 31, 2021

Package Language Transformer Tagger Parser NER en_core_web_trf English roberta-base 97.8 You can start off by cloning a pre-defined project template, adjust it to fit your needs, load in your data, train a pipeline, export it as a Python package, upload your outputs to a remote storage and share your results with your team.

Python 52

Python Machine Learning Machine Learning Data Science 52

Explosion

OCTOBER 15, 2017

In this post, we’ll introduce you to the new functionality, and finish with an example extension package, spacymoji. This is relevant for teams working with spaCy, but also for developers looking to publish their own packages, extensions and plugins. Luckily, the emoji package has us covered here. assert doc._.has_emoji

Natural Language Processing 52

Natural Language Processing Python Deep Learning Deep Learning 52

AWS Machine Learning Blog

AUGUST 15, 2023

We use the DirectoryLoader package in LangChain to load the text documents into the document loader: loader = DirectoryLoader("./data/demo-video-sagemaker-doc/", With this parameter, we can make the Whisper model see more context when doing inference on each chunk, which will lead to a more accurate result.

AWS 73

AWS ML ML AI 73

Explosion

NOVEMBER 21, 2019

sense2vec reloaded: the updated library sense2vec is a Python package to load and query vectors of words and multi-word phrases based on part-of-speech tags and entity labels. import spacy from spacy.pipeline import EntityRuler nlp = spacy.blank("en") ruler = EntityRuler(nlp).from_disk("./fashion_brands_patterns.jsonl") from_disk("./fashion_brands_patterns.jsonl")

Natural Language Processing 52

Natural Language Processing Data Scientist Machine Learning Machine Learning 52

Heartbeat

DECEMBER 13, 2023

dist-packages/wikipedia/__init__.py'>, py'>, top_k_results=3, lang='en', load_all_available_meta=False, doc_content_chars_max=4000)) And you can modify the fields above. For example, let’s change the description. description A wrapper around Wikipedia.

Deep Learning 52

Deep Learning Deep Learning ML ML 52