Explosion builds developer tools for AI, Machine Learning, and Natural Language Processing.
Project
Topics
Category
Tasks
Select...Code GenerationCoreference ResolutionDependency ParsingDistillationEmbeddings & VectorsEntity LinkingEvaluationImage ClassificationImage SegmentationLayout AnalysisLemmatizationNamed Entity RecognitionObject DetectionOptical Character Recognition (OCR)Part-of-Speech TaggingPII AnonymizationQuestion AnsweringRelation ExtractionRetrieval-Augmented Generation (RAG)Rule-Based MatchingSpan CategorizationText ClassificationText GenerationTokenizationWeak Supervision
Authors
Select...Adriane BoydÁkos KádárBasile DuraChung-Fan TsaiDamian RomeroDaniël de KokDuygu AltinokEdward SchmuhlHelena SteckmeisterIndia KerleInes MontaniKabir KhanLj MirandaMadeesh KannanMagdalena AniołMatthew HonnibalPaul O’Leary McCannPeter BaumgartnerPhilip VolletRaphael MitschRehan AhmedRichard HudsonRyan WesslenSofie Van LandeghemVictoria SlocumVincent D. WarmerdamVinit RavishankarWalter Henry
This talk highlights common pitfalls that occur when evaluating ML and NLP approaches. It provides comprehensive advice on how to set up a solid evaluation procedure in general, and dives into a few specific use-cases to demonstrate artificial bias that unknowingly can creep in.
In this post, Peter shares some lessons learned from chatting with practitioners about their NLP challenges, developing production-ready NLP pipelines for clients, and working with an open-source development team.
“What can you do to maximize the probability of success for your Machine Learning solution? Throughout my 15 years as a data scientist in academia, big pharma, and through consulting, one common theme has emerged: the most reliable predictor of success for any NLP or ML-based solution is whether or not you involve the data science team early on.”
Many people assume that working on an NLP project involves a lot of machine learning. Our experience is that it's much less about flowing tensors, and more about making a tailored solution. This blog post demonstrates how a typical spaCy project could be initiated, implemented, and executed towards a custom solution.
Explosion is pleased to announce a new development services offering, spaCy Tailored Pipelines. We’ll build you a custom natural language processing pipeline, delivered in a standardized format using spaCy’s projects system.