mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-28 19:06:33 +03:00
Merge branch 'master' into spacy.io
This commit is contained in:
Ines Montani
commit
85064b5c22
|
|
@ -7,7 +7,7 @@ def add_codes(err_cls):
|
|||
|
||||
class ErrorsWithCodes(err_cls):
|
||||
def __getattribute__(self, code):
|
||||
msg = super().__getattribute__(code)
|
||||
msg = super(ErrorsWithCodes, self).__getattribute__(code)
|
||||
if code.startswith("__"): # python system attributes like __class__
|
||||
return msg
|
||||
else:
|
||||
|
|
|
|||
|
|
@ -13,7 +13,7 @@ class PolishLemmatizer(Lemmatizer):
|
|||
# lemmatization for nouns
|
||||
def __init__(self, lookups, *args, **kwargs):
|
||||
# this lemmatizer is lookup based, so it does not require an index, exceptionlist, or rules
|
||||
super().__init__(lookups)
|
||||
super(PolishLemmatizer, self).__init__(lookups)
|
||||
self.lemma_lookups = {}
|
||||
for tag in [
|
||||
"ADJ",
|
||||
|
|
|
|||
|
|
@ -1132,7 +1132,7 @@
|
|||
"type": "education",
|
||||
"id": "spacy-course",
|
||||
"title": "Advanced NLP with spaCy",
|
||||
"slogan": "spaCy, 2019",
|
||||
"slogan": "A free online course",
|
||||
"description": "In this free interactive course, you'll learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.",
|
||||
"url": "https://course.spacy.io",
|
||||
"image": "https://i.imgur.com/JC00pHW.jpg",
|
||||
|
|
@ -1185,10 +1185,38 @@
|
|||
"youtube": "6zm9NC9uRkk",
|
||||
"category": ["videos"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "video-spacy-course",
|
||||
"title": "Advanced NLP with spaCy · A free online course",
|
||||
"description": "spaCy is a modern Python library for industrial-strength Natural Language Processing. In this free and interactive online course, you'll learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.",
|
||||
"url": "https://course.spacy.io/en",
|
||||
"author": "Ines Montani",
|
||||
"author_links": {
|
||||
"twitter": "_inesmontani",
|
||||
"github": "ines"
|
||||
},
|
||||
"youtube": "THduWAnG97k",
|
||||
"category": ["videos"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "video-spacy-course-de",
|
||||
"title": "Modernes NLP mit spaCy · Ein Gratis-Onlinekurs",
|
||||
"description": "spaCy ist eine moderne Python-Bibliothek für industriestarkes Natural Language Processing. In diesem kostenlosen und interaktiven Onlinekurs lernst du, mithilfe von spaCy fortgeschrittene Systeme für die Analyse natürlicher Sprache zu entwickeln und dabei sowohl regelbasierte Verfahren, als auch moderne Machine-Learning-Technologie einzusetzen.",
|
||||
"url": "https://course.spacy.io/de",
|
||||
"author": "Ines Montani",
|
||||
"author_links": {
|
||||
"twitter": "_inesmontani",
|
||||
"github": "ines"
|
||||
},
|
||||
"youtube": "K1elwpgDdls",
|
||||
"category": ["videos"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "video-intro-to-nlp-episode-1",
|
||||
"title": "Intro to NLP with spaCy",
|
||||
"title": "Intro to NLP with spaCy (1)",
|
||||
"slogan": "Episode 1: Data exploration",
|
||||
"description": "In this new video series, data science instructor Vincent Warmerdam gets started with spaCy, an open-source library for Natural Language Processing in Python. His mission: building a system to automatically detect programming languages in large volumes of text. Follow his process from the first idea to a prototype all the way to data collection and training a statistical named entity recogntion model from scratch.",
|
||||
"author": "Vincent Warmerdam",
|
||||
|
|
@ -1202,7 +1230,7 @@
|
|||
{
|
||||
"type": "education",
|
||||
"id": "video-intro-to-nlp-episode-2",
|
||||
"title": "Intro to NLP with spaCy",
|
||||
"title": "Intro to NLP with spaCy (2)",
|
||||
"slogan": "Episode 2: Rule-based Matching",
|
||||
"description": "In this new video series, data science instructor Vincent Warmerdam gets started with spaCy, an open-source library for Natural Language Processing in Python. His mission: building a system to automatically detect programming languages in large volumes of text. Follow his process from the first idea to a prototype all the way to data collection and training a statistical named entity recogntion model from scratch.",
|
||||
"author": "Vincent Warmerdam",
|
||||
|
|
@ -1213,6 +1241,34 @@
|
|||
"youtube": "KL4-Mpgbahw",
|
||||
"category": ["videos"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "video-intro-to-nlp-episode-3",
|
||||
"title": "Intro to NLP with spaCy (3)",
|
||||
"slogan": "Episode 2: Evaluation",
|
||||
"description": "In this new video series, data science instructor Vincent Warmerdam gets started with spaCy, an open-source library for Natural Language Processing in Python. His mission: building a system to automatically detect programming languages in large volumes of text. Follow his process from the first idea to a prototype all the way to data collection and training a statistical named entity recogntion model from scratch.",
|
||||
"author": "Vincent Warmerdam",
|
||||
"author_links": {
|
||||
"twitter": "fishnets88",
|
||||
"github": "koaning"
|
||||
},
|
||||
"youtube": "4V0JDdohxAk",
|
||||
"category": ["videos"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "video-intro-to-nlp-episode-4",
|
||||
"title": "Intro to NLP with spaCy (4)",
|
||||
"slogan": "Episode 4: Named Entity Recognition",
|
||||
"description": "In this new video series, data science instructor Vincent Warmerdam gets started with spaCy, an open-source library for Natural Language Processing in Python. His mission: building a system to automatically detect programming languages in large volumes of text. Follow his process from the first idea to a prototype all the way to data collection and training a statistical named entity recogntion model from scratch.",
|
||||
"author": "Vincent Warmerdam",
|
||||
"author_links": {
|
||||
"twitter": "fishnets88",
|
||||
"github": "koaning"
|
||||
},
|
||||
"youtube": "IqOJU1-_Fi0",
|
||||
"category": ["videos"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "video-spacy-irl-entity-linking",
|
||||
|
|
@ -1286,6 +1342,22 @@
|
|||
},
|
||||
"category": ["podcasts"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "podcast-init2",
|
||||
"title": "Podcast.__init__ #256: An Open Source Toolchain For NLP From Explosion AI",
|
||||
"slogan": "March 2020",
|
||||
"description": "The state of the art in natural language processing is a constantly moving target. With the rise of deep learning, previously cutting edge techniques have given way to robust language models. Through it all the team at Explosion AI have built a strong presence with the trifecta of SpaCy, Thinc, and Prodigy to support fast and flexible data labeling to feed deep learning models and performant and scalable text processing. In this episode founder and open source author Matthew Honnibal shares his experience growing a business around cutting edge open source libraries for the machine learning developent process.",
|
||||
"iframe": "https://cdn.podlove.org/web-player/share.html?episode=https%3A%2F%2Fwww.pythonpodcast.com%2F%3Fpodlove_player4%3D614",
|
||||
"iframe_height": 200,
|
||||
"thumb": "https://i.imgur.com/rpo6BuY.png",
|
||||
"url": "https://www.pythonpodcast.com/explosion-ai-natural-language-processing-episode-256/",
|
||||
"author": "Tobias Macey",
|
||||
"author_links": {
|
||||
"website": "https://www.podcastinit.com"
|
||||
},
|
||||
"category": ["podcasts"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "talk-python-podcast",
|
||||
|
|
@ -1348,6 +1420,18 @@
|
|||
},
|
||||
"category": ["podcasts"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "video-entity-linking",
|
||||
"title": "Training a custom entity linking mode with spaCy",
|
||||
"author": "Sofie Van Landeghem",
|
||||
"author_links": {
|
||||
"twitter": "OxyKodit",
|
||||
"github": "svlandeg"
|
||||
},
|
||||
"youtube": "8u57WSXVpmw",
|
||||
"category": ["videos"]
|
||||
},
|
||||
{
|
||||
"id": "adam_qas",
|
||||
"title": "ADAM: Question Answering System",
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ import Sidebar from '../components/sidebar'
|
|||
import Section from '../components/section'
|
||||
import Main from '../components/main'
|
||||
import Footer from '../components/footer'
|
||||
import { H3, Label, InlineList } from '../components/typography'
|
||||
import { H3, H5, Label, InlineList } from '../components/typography'
|
||||
import { YouTube, SoundCloud, Iframe } from '../components/embed'
|
||||
import { github, markdownToReact } from '../components/util'
|
||||
|
||||
|
|
@ -86,7 +86,10 @@ const UniverseContent = ({ content = [], categories, pageContext, location, mdxC
|
|||
<img
|
||||
src={`https://img.youtube.com/vi/${youtube}/0.jpg`}
|
||||
alt=""
|
||||
style={{ clipPath: 'inset(12.5% 0)' }}
|
||||
style={{
|
||||
clipPath: 'inset(12.9% 0)',
|
||||
marginBottom: 'calc(-12.9% + 1rem)',
|
||||
}}
|
||||
/>
|
||||
)
|
||||
return cover ? (
|
||||
|
|
@ -95,6 +98,13 @@ const UniverseContent = ({ content = [], categories, pageContext, location, mdxC
|
|||
<img src={cover} alt={title || id} />
|
||||
</Link>
|
||||
</p>
|
||||
) : data.id === 'videos' ? (
|
||||
<div>
|
||||
<Link key={id} to={url} hidden>
|
||||
{header}
|
||||
<H5>{title}</H5>
|
||||
</Link>
|
||||
</div>
|
||||
) : (
|
||||
<Card
|
||||
key={id}
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user