Element.io is highly recommended for privacy-conscious users, open-source enthusiasts, tech-savvy individuals, organizations seeking secure internal communication channels, and communities needing decentralized and customizable messaging solutions.
Pandas 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.
Based on our record, Pandas seems to be a lot more popular than Element.io. While we know about 219 links to Pandas, we've tracked only 1 mention of Element.io. 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.
I love how Matrix or its most popular client Element do not even get a mention. Source: about 2 years ago
The title undersells the change a bit in my opinion. By default, mastodon now encourages new users to sign-up on https://mastodon.social which has caused a bit of a kerfuffle in the fediverse. Personally, I'm largely ambivalent to the change; I understand the reasoning, and it's what https://element.io has been doing for https://matrix.org since the beginning. It is more than a bit of a sea-change though given the... - Source: Hacker News / about 2 years ago
We currently have the Matrix protocol, with client applications such as Element supporting it. We also have XMPP as another option. Generally more modern than IRC, these platforms are primarily developed as FOSS software. This makes it less likely for developers to impact their users negatively. However, despite these advantages, these platforms lack the refined user experience (addictiveness and stickiness) that... Source: about 2 years ago
Please DM me if you are interested in hiring me or have any questions at all. We will work via Element (https://element.io) voice/screen share calls, so please make sure you have a mic available. I look forward to hearing from you. Source: about 2 years ago
Your best bet is probably matrix, the most user friendly client iirc is element. Source: about 2 years ago
Libraries for data science and deep learning that are always changing. - Source: dev.to / 29 days 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 / about 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 / about 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 / 9 months ago
Matrix.org - Matrix is an open standard for decentralized persistent communication over IP.
NumPy - NumPy is the fundamental package for scientific computing with Python
Telegram - Telegram is a messaging app with a focus on speed and security. It’s superfast, simple and free.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Signal - Fast, simple & secure messaging. Privacy that fits in your pocket.
OpenCV - OpenCV is the world's biggest computer vision library