LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives.
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Pandas
NumPy
Scikit-learn
OpenCV
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Exploratory
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WEKA
CalyxOS
GrapheneOS
LineageOS
Android
Ubuntu Touch
e.foundation /e/
PureOS
postmarketOS
Pandas CalyxOSPandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.
Pandas might be a bit more popular than CalyxOS. We know about 219 links to it since March 2021 and only 191 links to CalyxOS. 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.
Libraries for data science and deep learning that are always changing. - Source: dev.to / about 2 months ago
# Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / 2 months ago
As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / 2 months ago
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 10 months ago
I use pixel 3 with https://calyxos.org/ as a home phone to play music, record videos, pictures etc. Calyxos is still providing extended support for 4a, but microG doesn't work as well compared to sandboxed google play services on grapheneos (which is use on my 7a). So if google services are not too important go ahead with calyxos. - Source: Hacker News / 5 months ago
For example https://androidauthority.com/grapheneos-3287030/ > "Even if you stomach the Pixel-only requirement" I have not and will not stomach that at all, nope! https://grapheneos.org/faq#supported-devices Nope! I wasn't paying attention, but if I remember, Alphabet/Google was funded to deploy/release Android operating system, and they also were financed to deploy some hardware phones before disappearing to let... - Source: Hacker News / over 1 year ago
I'm sure you did your research. I'm writing for other readers who are interested. There are a few alternatives, more can be found but this is a selection of the most prominent offerings. /e/OS: https://e.foundation/e-os/ GrapheneOS: https://grapheneos.org/ LineageOS: https://lineageos.org/ CalyxOS: https://calyxos.org/ PostmarketOS (based on Alpine Linux rather than Android): https://postmarketos.org/ (for some... - Source: Hacker News / over 1 year ago
Ironically, Pixels are the best for de-Googling. GrapheneOS requires a Pixel, as does CalyxOS for the most part. If you don't want your money going to Google, a used/refurb Pixel gets around that in my opinion. Source: almost 2 years ago
Oh I see makes sense, one closed system needs another 😅 but if you look at Android, look at https://grapheneos.org/ and https://calyxos.org/. Source: about 2 years ago
NumPy - NumPy is the fundamental package for scientific computing with Python
GrapheneOS - GrapheneOS is an open source privacy and security focused mobile OS with Android app compatibility.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
LineageOS - Operating system for smartphones and tablet computers, based on the Android
OpenCV - OpenCV is the world's biggest computer vision library
Android - Android is an open source mobile operating system initially released by Google in 2008 and has since become of the most widely used operating systems on any platform.