Like many of you, I'm incredibly disappointed by DataCamp. I wanted to make a free version of my spaCy course so you don't have to sign up for their service – and ended up building my own interactive app. Powered by the awesome @mybinderteam & @gatsbyjs 💖
Ines Montani
3,674 posts
Joined May 2008
- TIL: @firefox comes with a built-in JSON viewer, which automatically transforms JSON-formatted files and API responses into a collapsible, searchable and syntax-highlighted tree 😍
- Someone asked me for tips in the comments, so I might as well make this a thread. Here are my personal recommendations for how to get started with front-end development, APIs, CSS, React, UI design and more 👇
- .@streamlit is very cool 🔥✨ It took me hardly any time and around 100 lines of Python to build an interactive @spacy_io model visualizer, complete with dependencies, named entities, similarity and more. 📄 Code: gist.github.com/ines/b320cb844… ▶️ $ streamlit run streamlit_spacy.py
00:00 - The video of my @europython 2018 keynote is now live: "How to Ignore Most Startup Advice and Build a Decent Software Business" ✨ For everyone who's been asking for more readings along the same lines, here are some classics (thread)
- Looking to self-publish your own interactive online courses? 🎓🐍 It's now even easier, thanks to the amazing @hayleyfboyce, who contributed a super detailed guide for my little open-source framework. Plus a Dockerfile for faster setup! 📖 Read it here: ines.github.io/course-starter…
- I'm trying something new today! 💥 Had a lot of fun giving my keynote talk at @pyconcolombia yesterday, so here it is – in tweet form. One tweet per slide. The future of NLP in Python (thread) Full slide deck: speakerdeck.com/inesmontani/th…
- This came up the other day, so here's a quick guide to fast processing with spaCy! Full pipeline: 🐌 docs = [nlp(text) for text in texts] 🔥 docs = list(nlp.pipe(texts)) Tokenizer only: 🐌 docs = [nlp.tokenizer(text) for text in texts] 🔥 docs = list(nlp.tokenizer.pipe(texts))
- Built this wrapper for the new @StanfordNLP library so you can use their state-of-the-art Universal Dependencies models directly in your @spacy_io pipeline 💘 github.com/explosion/spac…
- Today we also started open-sourcing some of our datasets & NLP example projects! Includes 1k+ annotated examples each, train/eval scripts, results, data vizualizers & some powerful tok2vec weights trained on Reddit to initialize models. 💝 Repo: github.com/explosion/proj…You’re unable to view this Post because this account owner limits who can view their Posts. Learn more
- I've started putting together flowcharts for solving various NLP problems with prodi.gy (and beyond). Obviously none of this is foolproof – it's just a summary of our usual advice. Here's the first one for Named Entity Recognition! 📥 PDF: prodi.gy/docs/pdfs/prod…
- Here are the slides for my @PyDataLondon keynote on LLMs from prototype to production ✨ Including: ◾ visions for NLP in the age of LLMS ◾ a case for LLM pragmatism ◾ solutions for structured data ◾ @spacy_io LLM + prodi.gy speakerdeck.com/inesmontani/la…













