How to Use Apple Vision Framework via PyObjC for Text Recognition
THis article discusses how to use the Vision framework via PyObjC, which allows you to use Objective-C frameworks from Python. The Vision framework is a machine learning framework that can be used to perform tasks such as face detection, object detection, and text recognition.
https://yasoob.me/posts/how-to-use-vision-framework-via-pyobjc/
THis article discusses how to use the Vision framework via PyObjC, which allows you to use Objective-C frameworks from Python. The Vision framework is a machine learning framework that can be used to perform tasks such as face detection, object detection, and text recognition.
https://yasoob.me/posts/how-to-use-vision-framework-via-pyobjc/
yasoob.me
How to Use Apple Vision Framework via PyObjC for Text Recognition - Yasoob Khalid
Introduction This post has been sitting in my drafts folder for a long time. Sometime earlier this year I saw a job posting where someone wanted to use Apple’s vision framework to do text recognition. I wasn’t interested in the job but I was curious about…
Towards a new SymPy: Part 1 - Outline
This first post will outline the structure of the foundations of a computer algebra system (CAS) like SymPy, describe some problems SymPy currently has and what can be done to address them. Then subsequent posts will focus in more detail on particular components and the work that has been done and what should be done in the future.
https://oscarbenjamin.github.io/blog/czi/post1.html
This first post will outline the structure of the foundations of a computer algebra system (CAS) like SymPy, describe some problems SymPy currently has and what can be done to address them. Then subsequent posts will focus in more detail on particular components and the work that has been done and what should be done in the future.
https://oscarbenjamin.github.io/blog/czi/post1.html
How the Python Dataframe Interchange Protocol Makes Life Better
In this article, we answer three questions about the Python Dataframe Interchange Protocol: What it is + what problems it solves; how it works; and how extensively it's been adopted.
https://ponder.io/how-the-python-dataframe-interchange-protocol-makes-life-better/
In this article, we answer three questions about the Python Dataframe Interchange Protocol: What it is + what problems it solves; how it works; and how extensively it's been adopted.
https://ponder.io/how-the-python-dataframe-interchange-protocol-makes-life-better/
Ponder
How the Python Dataframe Interchange Protocol Makes Life Better
In this article, we answer three questions about the Python Dataframe Interchange Protocol: What it is + what problems it solves; how it works; and how extensively it's been adopted.
Add database search with Django and HTMX
We'll create a fast and simple database search using Django and HTMX. It's easy and fast to do with HTMX. There'll be 6 steps.
https://www.photondesigner.com/articles/database-search-django-htmx
We'll create a fast and simple database search using Django and HTMX. It's easy and fast to do with HTMX. There'll be 6 steps.
https://www.photondesigner.com/articles/database-search-django-htmx
Photondesigner
Add instant database search with Django and HTMX 🕵️
Search server-side with speed.
Deploying Django with Kamal (mrsk)
If you just want to deploy containers on a remote machine, Kamal might be a nice addition to your toolbelt. It automates many common steps when deploying containers to one or more remote machines, without introducing the complexity of something like Kubernetes or having to use a managed service.
https://anthonynsimon.com/blog/kamal-deploy/
If you just want to deploy containers on a remote machine, Kamal might be a nice addition to your toolbelt. It automates many common steps when deploying containers to one or more remote machines, without introducing the complexity of something like Kubernetes or having to use a managed service.
https://anthonynsimon.com/blog/kamal-deploy/
Anthonynsimon
Deploying Django with Kamal
In this post I'll walk you through my template to deploy a Django monolith using Kamal (mrsk), but you could also adapt it for Rails or Laravel.
Processing a 250 TB dataset with Coiled, Dask, and Xarray
The authors successfully processed 250TB of geospatial cloud data in 20 minutes using Xarray, Dask, and Coiled, highlighting the challenges and optimizations involved, all while keeping the cost at approximately $25. This achievement demonstrates the feasibility of large-scale data processing, exposes scalability issues, and explores cost-efficient strategies for such tasks.
https://blog.coiled.io/blog/coiled-xarray.html
The authors successfully processed 250TB of geospatial cloud data in 20 minutes using Xarray, Dask, and Coiled, highlighting the challenges and optimizations involved, all while keeping the cost at approximately $25. This achievement demonstrates the feasibility of large-scale data processing, exposes scalability issues, and explores cost-efficient strategies for such tasks.
https://blog.coiled.io/blog/coiled-xarray.html
Coiled
Processing a 250 TB dataset with Coiled, Dask, and Xarray
We processed 250TB of geospatial cloud data in twenty minutes on the cloud with Xarray, Dask, and Coiled. We do this to demonstrate scale and to think about costs. Many people use Dask with Xarray ...
blip-caption
Generate captions for images with Salesforce BLIP.
https://github.com/simonw/blip-caption
Generate captions for images with Salesforce BLIP.
https://github.com/simonw/blip-caption
GitHub
GitHub - simonw/blip-caption: Generate captions for images with Salesforce BLIP
Generate captions for images with Salesforce BLIP. Contribute to simonw/blip-caption development by creating an account on GitHub.
Medusa
Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads.
https://github.com/FasterDecoding/Medusa
Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads.
https://github.com/FasterDecoding/Medusa
GitHub
GitHub - FasterDecoding/Medusa: Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads
Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads - FasterDecoding/Medusa
Litestar
Litestar is a powerful, flexible yet opinionated ASGI framework, focused on building APIs, and offers high-performance data validation and parsing, dependency injection, first-class ORM integration, authorization primitives, and much more that's needed to get applications up and running.
https://github.com/litestar-org/litestar
Litestar is a powerful, flexible yet opinionated ASGI framework, focused on building APIs, and offers high-performance data validation and parsing, dependency injection, first-class ORM integration, authorization primitives, and much more that's needed to get applications up and running.
https://github.com/litestar-org/litestar
GitHub
GitHub - litestar-org/litestar: Production-ready, Light, Flexible and Extensible ASGI API framework | Effortlessly Build Performant…
Production-ready, Light, Flexible and Extensible ASGI API framework | Effortlessly Build Performant APIs - litestar-org/litestar
How to add serverless functions to Django in 6 minutes (with HTMX and AWS Lambda)
This article discusses the integration of serverless functions with Django, highlighting how developers can leverage the benefits of serverless computing for specific tasks in a Django application. It explores the advantages of serverless architecture and provides practical insights for implementation.
https://www.photondesigner.com/articles/serverless-functions-django
This article discusses the integration of serverless functions with Django, highlighting how developers can leverage the benefits of serverless computing for specific tasks in a Django application. It explores the advantages of serverless architecture and provides practical insights for implementation.
https://www.photondesigner.com/articles/serverless-functions-django
Photondesigner
How to add serverless functions with Django in 6 mins (with HTMX and AWS Lambda) 🧠
Add serverless functions. Banish background worker mess.
ludwig-ai / ludwig
Low-code framework for building custom LLMs, neural networks, and other AI models
https://github.com/ludwig-ai/ludwig
Low-code framework for building custom LLMs, neural networks, and other AI models
https://github.com/ludwig-ai/ludwig
GitHub
GitHub - ludwig-ai/ludwig: Low-code framework for building custom LLMs, neural networks, and other AI models
Low-code framework for building custom LLMs, neural networks, and other AI models - ludwig-ai/ludwig
Galactic
Galactic provides cleaning and curation tools for massive unstructured text datasets. It's designed to help you curate fine-tuning datasets, create document collections for retrieval-augmented generation (RAG), and even perform deduplication of web-scale datasets for LLM pre-training. This
https://github.com/taylorai/galactic
Galactic provides cleaning and curation tools for massive unstructured text datasets. It's designed to help you curate fine-tuning datasets, create document collections for retrieval-augmented generation (RAG), and even perform deduplication of web-scale datasets for LLM pre-training. This
https://github.com/taylorai/galactic
GitHub
GitHub - taylorai/galactic: data cleaning and curation for unstructured text
data cleaning and curation for unstructured text. Contribute to taylorai/galactic development by creating an account on GitHub.
HomeHarvest
Python package for real estate scraping, supporting Zillow, Realtor.com & Redfin.
https://github.com/ZacharyHampton/HomeHarvest
Python package for real estate scraping, supporting Zillow, Realtor.com & Redfin.
https://github.com/ZacharyHampton/HomeHarvest
GitHub
GitHub - ZacharyHampton/HomeHarvest: Python package for scraping real estate property data
Python package for scraping real estate property data - ZacharyHampton/HomeHarvest