・SPACY v3: State-of-the-art NLP from Prototype to Production[27:56]
・SPACY v3: Design concepts explained (behind the scenes)[24:42]
・Coreference Resolution in spaCy[12:02]
・SPACY v3: Custom trainable relation extraction component[38:11]
・Training a custom ENTITY LINKING model with spaCy[28:24]
・SPACY'S ENTITY RECOGNITION MODEL: incremental parsing with Bloom embeddings \u0026 residual CNNs[54:54]
・Training a NAMED ENTITY RECOGNITION MODEL with Prodigy and Transfer Learning[40:28]
・IMAGE CAPTIONING ANNOTATION with Prodigy \u0026 PyTorch: custom scriptable machine learning annotation[39:25]
・TRAINING AN INSULTS CLASSIFIER with Prodigy in ~1 hour[27:16]
・PRODIGY v1.12: OpenAI integration, Prompt Engineering, Task Routers, Deployment Docs and more![23:28]
・Finding Video Games with Sense2Vec[34:06]
・Introducing Span Categorization in Prodigy and spaCy[13:33]
・PRODIGY v1.13: SPACY-LLM support, more LLM backends, better prompts and local model support![14:15]
・MODELS AS ANNOTATORS in Prodigy v1.13.1 - Focus when models disagree![21:13]
・Bulk Labelling and Prodigy[22:42]
・Finetuning and Bulk Labelling IMAGES with Prodigy[38:08]
・PRODIGY v1.10: Dependencies, relations, audio, video, extended NER and image annotation \u0026 lots more[17:39]
・Finding BAD LABELS for TEXT CLASSIFICATION with Jupyter and Prodigy[45:18]
・Streaming spaCy (Feb 6, 2025): Updating Confection for Python 3.13 and more[43:11]
・dotAI 2024 - Ines Montani - Reality is not an end-to-end prediction problem[18:28]
・Ines Montani - A practical guide to human-in-the-loop distillation | Pydata London 2024[34:04]
・The AI Revolution Will Not Be Monopolized: How open-source beats economies of scale, even for LLMs[29:35]
・Ines Montani \u0026 Ryan Wesslen - Half hour of labeling power: Can we beat GPT? | PyData NYC 2023[45:17]
・How Many Labelled Examples Do You Need for a BERT-sized Model to Beat GPT4 on Predictive Tasks?[28:25]
・Large Language Models: From Prototype to Production — Ines Montani[40:21]
・Ines Montani Keynote - Applied NLP Thinking[18:40]
・Ines Montani: Incorporating GPT-3 into practical NLP workflows[45:09]
・Sofie Van Landeghem- How to Avoid structural biases in evaluating your Machine Learning/NLP projects[39:03]
・Herding LLMs Towards Structured NLP[31:16]
・Matthew Honnibal - Designing for tomorrow's programming workflows[26:42]
・PyLadies Entrepreneurs and Career Development[43:28]
・Accélérer sa Carrière avec l'IA Open-Source 🇬🇧[45:42]
・The NLP and AI Revolution with spaCy Creators Ines Montani and Matthew Honnibal[58:08]
・Exploring the AI Nexus with the Mind Behind Spacy | Leading with Data 39[53:53]
・SE Radio 611: Ines Montani on Natural Language Processing[16:31]
・Talk Python: Building a Data Science Startup - Talk Python to Me Ep.300[58:41]
・Interview w Ines Montani | Spacy, NLP \u0026 Open Source Frameworks | Explosion.ai, Thinc.ai \u0026 Prodi.gy[52:00]
・Intro to NLP with spaCy (1): Detecting programming languages | Episode 1: Data exploration[32:27]
・Intro to NLP with spaCy (2): Detecting programming languages | Episode 2: Rule-based matching[24:25]
・Intro to NLP with spaCy (3): Detecting programming languages | Episode 3: Evaluation[30:01]
・Intro to NLP with spaCy (4): Detecting programming languages | Episode 4: Named Entity Recognition[30:54]
・Intro to NLP with spaCy (5): Detecting programming languages | Episode 5: Rules vs. Machine Learning[30:26]
・Intro to NLP with spaCy (6): Detecting programming languages | Episode 6: Moving to spaCy v3[22:58]
・Advanced NLP with spaCy · A free online course[47:31]
・Modernes NLP mit spaCy · Ein Gratis-Onlinekurs[52:32]
・NLP avanzado con spaCy · Un curso en línea gratis[50:32]
・Sebastian Ruder: Transfer Learning in Open-Source Natural Language Processing (spaCy IRL 2019)[31:24]
・Giannis Daras: Improving sparse transformer models for efficient self-attention (spaCy IRL 2019)[20:14]
・Peter Baumgartner: Applied NLP: Lessons from the Field (spaCy IRL 2019)[18:44]
・Justina Petraitytė: Lessons learned in helping ship conversational AI assistants (spaCy IRL 2019)[23:49]
・Yoav Goldberg: The missing elements in NLP (spaCy IRL 2019)[30:27]
・Sofie Van Landeghem: Entity linking functionality in spaCy (spaCy IRL 2019)[20:08]
・Guadalupe Romero: Rethinking rule-based lemmatization (spaCy IRL 2019)[14:49]
・Mark Neumann: ScispaCy: A spaCy pipeline \u0026 models for scientific \u0026 biomedical text (spaCy IRL 2019)[19:00]
・Patrick Harrison: Financial NLP at S\u0026P Global (spaCy IRL 2019)[21:43]
・McKenzie Marshall: NLP in Asset Management (spaCy IRL 2019)[20:32]
・David Dodson: spaCy in the News: Quartz's NLP pipeline (spaCy IRL 2019)[20:57]
・Matthew Honnibal \u0026 Ines Montani: spaCy and Explosion: past, present \u0026 future (spaCy IRL 2019)[54:14]
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