GitHub for Mobile Reviews

Seaborn Reviews

GitHub for Mobile mentions (6)

• Join GitHub Education

  Secure your GitHub account with two-factor authentication. (It is recommended to use the GitHub Mobile app.). - Source: dev.to / about 2 years ago

• Learning JS on Android

  If Git is the #1 Version Control System, GitHub is the #1 cloud service for Git. It allows code issues reporting, code-reviewing and, most importantly, it will keeps the repository on the cloud if your cellphone suddenly explodes. Microsoft has been doing a great job on the GitHub app: It has most of the features available on GitHub desktop. Edit files, submit, approve and comment on pull requests, everything from... - Source: dev.to / over 4 years ago

• GitOps with NSX Advanced Load Balancer and Jenkins

  Peer Review : Instead of meetings, advance reading, some kind of Microsoft Office document versioning and comments, a git pull request is fundamentally better in every way, and easier too. GitHub even has a mobile app to make peer review as frictionless as possible. - Source: dev.to / over 4 years ago

• Best Mobile Note-Taking Apps for Markdown

  Users may also be interested in future development around the GitHub mobile client, which currently does not support being able to edit or contribute new files. For now, people can use the app to post "LGTM" to PRs, add thumbs-down emojis to issues, and get notified when your PRs are rejected. - Source: dev.to / over 4 years ago

• CNC 2021 – Write More Challenge – First Mission

  Interacting with GitHub from your mobile : Technical post – Showing how to do some common procedure using the official GitHUb app on a mobile (Android) – Example of processes : Modifying a file, Creating a new branch, creating a new Pull Request, Reviewing a Pull Request, merging a Pull Request – Nice to have: Some small videos for each procedures to allow the user the see them done "live" – Easy to write but I am... - Source: dev.to / about 5 years ago

Seaborn mentions (37)

• How I Hacked Uber’s Hidden API to Download 4379 Rides

  Below are the key insights. If you want to see the Python code I used to do this analysis and generate the charts using Seaborn, you can find my full analysis Jupyter notebook on my Github repo here: Tip Analysis.ipynb. - Source: dev.to / over 1 year ago

• Scientific Visualization: Python and Matplotlib, by Nicolas Rougier

  Additionally, Seaborn (https://seaborn.pydata.org/) is a great mention for people that want to use Matplotlib with better default aesthetics, amongst other conveniences: "Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.". - Source: Hacker News / almost 2 years ago

• Data Visualisation Basics

  Seaborn: built on top of matplotlib, adds a number of functions to make common statistical visualizations easier to generate. - Source: dev.to / almost 2 years ago

• Useful Python Libraries for AI/ML

  Pandas - The standard data analysis and manipulation tool Numpy - scientific computing library Seaborn - statistical data visualization Sklearn - basic machine learning and predictive analysis CausalML - a suite of uplift modeling and causal inference methods PyTorch - professional deep learning framework PivotTablejs - Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook LazyPredict - build... - Source: dev.to / almost 2 years ago

• Essential Deep Learning Checklist: Best Practices Unveiled

  How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago