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CloudShell VS Kaggle

Compare CloudShell VS Kaggle and see what are their differences

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CloudShell logo CloudShell

Cloud Shell is a free admin machine with browser-based command-line access for managing your infrastructure and applications on Google Cloud Platform.

Kaggle logo Kaggle

Kaggle offers innovative business results and solutions to companies.
  • CloudShell Landing page
    Landing page //
    2023-07-12
  • Kaggle Landing page
    Landing page //
    2023-04-18

CloudShell features and specs

  • Integrated Environment
    CloudShell provides a fully integrated development environment directly within your browser, including access to Google Cloud resources, pre-installed Google Cloud SDK, and other useful tools.
  • Convenience
    Because it's browser-based, there is no need to install or configure anything locally, which can save considerable setup time and eliminate environment inconsistencies.
  • Security
    Operating within Google's infrastructure can add layers of security, including secure connection to cloud resources and less risk of exposing local machines to vulnerabilities.
  • Access to Project Resources
    Directly connects to Google Cloud resources associated with your account, making it easy to manage and deploy applications within your cloud environment.
  • Scalability
    Seamlessly scalable environment that can handle different workloads without performance degradation.
  • Persistent Storage
    CloudShell offers persistent storage, allowing users to save their work and configurations, which are available in future sessions.
  • Pre-installed Tools
    Includes a range of pre-installed tools, such as git, gcloud SDK, and language libraries, enabling efficient development and deployment workflows.

Possible disadvantages of CloudShell

  • Resource Limits
    CloudShell has usage limits, including limited disk space and CPU, which may not be sufficient for all types of workloads, particularly resource-intensive tasks.
  • Inactive Use Timeouts
    Sessions that are inactive for a period of time may be automatically terminated, which can disrupt ongoing work.
  • Dependency on Internet Connection
    Being a cloud-based solution, a stable internet connection is required. Any disruption in connectivity can hamper development and deployment processes.
  • Latency Issues
    Depending on your geographical location, there may be latency issues which can affect performance and response times.
  • Limited Customization
    While CloudShell provides many pre-installed tools, users have limited control over the environment compared to a locally managed development setup.
  • Paid Subscription Needed for Extensive Use
    Beyond the free tier, extensive usage of CloudShell resources may incur additional costs, which can add up depending on the scale and nature of the tasks.
  • Learning Curve
    New users who are not familiar with Google Cloud's ecosystem may face an initial learning curve to fully leverage CloudShell's capabilities.

Kaggle features and specs

  • Community
    Kaggle has a vibrant community of data scientists and machine learning practitioners who actively collaborate, share knowledge, and support each other.
  • Competitions
    The platform hosts numerous competitions that allow users to test their skills on real-world problems, often with monetary prizes and recognition.
  • Datasets
    Kaggle offers a vast repository of datasets that are readily available for analysis and can be used to practice and build models.
  • Kernels
    Users can share and run code in the cloud using Kaggle Kernels, which provide a collaborative environment for analysis and model development.
  • Learning Resources
    Kaggle provides numerous tutorials, courses, and micro-courses to help beginners and advanced users improve their skills in data science and machine learning.

Possible disadvantages of Kaggle

  • Steep Learning Curve
    For beginners, the breadth and depth of content and tools available on Kaggle can be overwhelming, making it difficult to know where to start.
  • Competition Pressure
    While competitions can be motivating, they can also be stressful and may require a significant time investment, which can be discouraging for some users.
  • Public Exposure
    Submissions and code are often public, which may not be suitable for all users, especially those uncomfortable with sharing their work or making mistakes publicly.
  • Limited Real-world Application
    Some competitions and datasets are heavily curated or simplified, which may not fully represent the complexities and messiness of real-world data science problems.
  • Resource Limitations
    Free tier users have limited computational resources on Kaggle Kernels, which can be a constraint for more complex models or larger datasets.

CloudShell videos

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Kaggle videos

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How to use Kaggle ?

More videos:

  • Review - Kaggle Live-Coding: Code Reviews! Class imbalanced in Python | Kaggle
  • Review - Kaggle Live-Coding: Code Reviews! | Kaggle

Category Popularity

0-100% (relative to CloudShell and Kaggle)

CloudShell

Kaggle

Text Editors
100 100%
Text Editors
0% 0
Data Collaboration
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Data Collaboration
100% 100
IDE
100 100%
IDE
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare CloudShell and Kaggle

CloudShell Reviews

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Kaggle Reviews

Top 10 Developer Communities You Should Explore
Kaggle is an online platform that hosts data science competitions, provides datasets for analysis and machine learning projects, and offers a collaborative environment for data scientists and machine learning enthusiasts. It was founded in 2010 and has become a prominent platform for individuals and teams to showcase their data science skills, learn from one another, and...
Source: www.qodo.ai
The Best ML Notebooks And Infrastructure Tools For Data Scientists
Kaggle, an online community of data scientists, hosts Jupyter notebooks for R and Python. Kaggle Notebooks can be created and edited via a notebook editor with an editing window, a console, and a setting window. Kaggle hosts a vast number of publicly available datasets. Besides, you can also output files from a different Notebook or upload your own dataset. Kaggle comes with...
Source: analyticsindiamag.com
Top 25 websites for coding challenge and competition [Updated for 2021]
Kaggle is famous for being the place where data scientists collaborate and compete with each other. But they also have a platform called Kaggle Learn where micro-courses are provided. They are mini-courses where data scientists can learn practical data skills that they can apply immediately. They call it the fastest (and most fun) way to become a data scientist or improve...
Source: towardsdatascience.com

Social recommendations and mentions

Based on our record, Kaggle should be more popular than CloudShell. It has been mentiond 101 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.

CloudShell mentions (12)

  • Intro to the YouTube APIs: searching for videos
    Command-line (gcloud) -- Those who prefer working in a terminal can enable APIs with a single command in the Cloud Shell or locally on your computer if you installed the Cloud SDK which includes the gcloud command-line tool (CLI) and initialized its use. If this is you, issue this command to enable the API: gcloud services enable youtube.googleapis.com Confirm all the APIs you've enabled with this command:... - Source: dev.to / 9 months ago
  • Explore the world with Google Maps APIs
    Gcloud/command-line - Finally, for those more inclined to using the command-line, you can enable APIs with a single command in the Cloud Shell or locally on your computer if you installed the Cloud SDK (which includes the gcloud command-line tool [CLI]) and initialized its use. If this is you, issue the following command to enable all three APIs: gcloud services enable geocoding-backend.googleapis.com... - Source: dev.to / 12 months ago
  • Getting started with the Google Cloud CLI interactive shell for serverless developers
    While you might find that using the Google Cloud online console or Cloud Shell environment meets your occasional needs, for maximum developer efficiency you will want to install the Google Cloud CLI (gcloud) on your own system where you already have your favorite editor or IDE and git set up. - Source: dev.to / over 2 years ago
  • Cloud desktops aren't as good as you'd think
    Here is the product https://cloud.google.com/shell It has a quick start guide and docs. - Source: Hacker News / over 2 years ago
  • I do not have a personal laptop. Should I use my school's library computers to start learning or just wait until I get a laptop?
    If you are worried about creating other accounts etc - you can just use your gmail account with https://cloud.google.com/shell and that gives you a very small vm and a coding environment (replit or colab are way better than this though). Source: about 3 years ago
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Kaggle mentions (101)

  • Machine learning for web developers
    Before you even build a model, you are going to need some kind of dataset. Usually a CSV or JSON file. You can build your own dataset from scratch using your own data, scrape data from somewhere, or use Kaggle. - Source: dev.to / 5 months ago
  • How to Make Money From Coding: A Beginner-Friendly Practical Guide
    Kaggle: For data science and machine learning competitions. - Source: dev.to / 9 months ago
  • Need help with Python / Research Project
    Need help with last minute python project (due today). Project involves choosing a dataset from kaggle.com to analyze and creating questions to answer through analyzing the data. I have a pdf file of the project guidelines if you want more details. Also on a budget. Source: almost 2 years ago
  • Required coding skills needed for DS
    Next, you can do basic analysis of datasets in Python using libraries like pandas and scikit-learn. There's a lot of example datasets on kaggle.com. Source: almost 2 years ago
  • Freelance Working
    Also look into kaggle.com and participate in competitions, etc. This will be something you can show on your CV as real-world-experience while boosting your skills. Source: almost 2 years ago
View more

What are some alternatives?

When comparing CloudShell and Kaggle, you can also consider the following products

GitHub Codespaces - GItHub Codespaces is a hosted remote coding environment by GitHub based on Visual Studio Codespaces integrated directly for GitHub.

Colaboratory - Free Jupyter notebook environment in the cloud.

CodeTasty - CodeTasty is a programming platform for developers in the cloud.

Numerai - Hedge fund that crowdsources market trading from AI programmers over the Internet

Dirigible - Dirigible is a cloud development toolkit providing both development tools and runtime environment.

DataSource.ai - Community-funded data science tournaments

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