đź’« Industrial-strength Natural Language Processing (NLP) in Python - explosion/spaCy
Taking machine learning models into production for video analytics doesn’t have to be hard. A pipeline with reasonable efficiency can be created very quickly just by plugging together the right librar ...
When you finish a new version of your Python application, how do you build and deploy it? Do you change the version number, upload the new files to production, and be done with it? There are better…
This is a guest post by the data science team at Bayer Crop Science. Farmers have always collected and evaluated a large amount of data with each growing season: seeds planted, crop protection inputs ...
spaCy v3.0 is going to be a huge release! It features new transformer-based pipelines that get spaCy's accuracy right up to the current state-of-the-art, and a new workflow system to help you take pro ...
Angular CLI schematics offer us a way to add, scaffold and update app-related files and modules. You'll be guided through some common but currently undocumented helper functions you can use to achieve ...
Let us know how do you think about this newsletter or want to add new topics or keywords
Release v3.0.0: Transformer-based pipelines, new training system, project templates, custom models, improved component API, type hints & lots more · explosion/spaCy
By paulbridger -
2020-09-23
A Simple and Flexible Pytorch Video Pipeline
Automatically Build and Deploy Your Python Application in 4 Easy Steps
By Amazon Web Services -
2021-01-05
Accelerating MLOps at Bayer Crop Science with Kubeflow Pipelines and Amazon SageMaker
By Explosion -
2020-10-15
Introducing spaCy v3.0 nightly
By inDepthDev -
2021-01-24
Speed up your Angular schematics development with useful helper functions - Angular inDepth