Supabase
Firebase
Next.js
AppWrite
Vercel
Hasura
Etebase
Strapi
NumPy
Pandas
OpenCV
Scikit-learn
Dataiku
Exploratory
htm.java
WEKA
SupabaseBased on our record, Supabase should be more popular than NumPy. It has been mentiond 439 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In such cases Supabase is a great open-source alternative to setting up a custom backend, and integrating it into an Angular app is fairly simple, given the existing supabase dependencies like @supabase/supabase-js. The only prerequisite to make it work is initialising a supabase project and generating an API key. - Source: dev.to / 5 days ago
Supabase is a database for storage and authentication - available for free. - Source: dev.to / 11 days ago
In this article, we'll show you how to create a handy web app that can summarize the content of any web page. Using Next.js for a smooth and fast web experience, LangChain for processing language, OpenAI for generating summaries, and Supabase for managing and storing vector data, we'll build a powerful tool together. - Source: dev.to / 14 days ago
I see it differently. In the 25 years I've been working in this industry I see a welcome trend toward doing more in the database, such that the impedance mismatch dissipates: https://gist.github.com/cpursley/c8fb81fe8a7e5df038158bdfe0f06dbb https://supabase.com/ One way to eliminate the Java-SQL impedance (for example) mismatch is to delete Java altogether, along with JOOQ,... - Source: Hacker News / about 1 month ago
My initial, now long abandoned, plan was to use Next/Nuxt to create the front-end and have the back-end be in Python, to allow me to use the recipe-scrapers library, and to use Supabase to organise the database of users and their collection of recipes, and allow the users to enter a list of ingredients and be presented with a selection of recipes from their own curated collection that contained those recipes,... - Source: dev.to / about 1 month ago
How to Accomplish: Develop a script that iterates over the image database, preprocesses each image according to the model's requirements (e.g., resizing, normalization), and feeds them into the model for prediction. Ensure the script can handle large datasets efficiently by implementing batch processing. Use libraries like NumPy or Pandas for data management and TensorFlow or PyTorch for model inference. Include... - Source: dev.to / 22 days ago
NumPy: This library is fundamental for handling arrays and matrices, such as for operations that involve image data. NumPy is used to manipulate image data and perform calculations for image transformations and mask operations. - Source: dev.to / 23 days ago
NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation. - Source: dev.to / 28 days ago
This guide covers the basics of NumPy, and there's much more to explore. Visit numpy.org for more information and examples. - Source: dev.to / 30 days ago
Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 10 months ago
Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Next.js - A small framework for server-rendered universal JavaScript apps
OpenCV - OpenCV is the world's biggest computer vision library
AppWrite - Appwrite provides web and mobile developers with a set of easy-to-use and integrate REST APIs to manage their core backend needs.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.