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Kaggle VS Kaggle Notebooks

Compare Kaggle VS Kaggle Notebooks and see what are their differences

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Kaggle logo Kaggle

Kaggle offers innovative business results and solutions to companies.

Kaggle Notebooks logo Kaggle Notebooks

Kaggle Notebooks are a computational environment that enables reproducible and collaborative analysis.
  • Kaggle Landing page
    Landing page //
    2023-04-18
  • Kaggle Notebooks Landing page
    Landing page //
    2023-11-11

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.

Kaggle Notebooks features and specs

No features have been listed yet.

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

Kaggle Notebooks videos

No Kaggle Notebooks videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Kaggle and Kaggle Notebooks)

Kaggle

Kaggle Notebooks

Data Collaboration
100 100%
Data Collaboration
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Data Science Tools
0 0%
Data Science Tools
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 Kaggle and Kaggle Notebooks

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

Kaggle Notebooks Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Kaggle Notebooks is a cloud-based notebook platform for data science and machine learning enthusiasts. It provides access to hardware resources for running machine learning and deep learning models (think GPUs and TPUs).
Source: lakefs.io
7 best Colab alternatives in 2023
Kaggle is best known for its data science competitions, but it also offers a cloud-based computation environment known as Kaggle Kernels. Like Colab, it provides free access to GPUs and supports Python, R, and Julia languages. It is also deeply integrated with other Kaggle features, providing direct access to a wealth of datasets and community notebooks, making it an...
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Kaggle Notebooks is a cloud-based notebook alternative platform for data science enthusiasts and machine learning. Like Google Colab, Kaggle Notebooks offers powerful hardware resources, including GPUs and TPUs, for running machine learning and deep learning models. It also offers a number of other useful features, such as integration with the Kaggle API, support for version...
Source: noteable.io

Social recommendations and mentions

Based on our record, Kaggle seems to be more popular. 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.

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 / 10 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

Kaggle Notebooks mentions (0)

We have not tracked any mentions of Kaggle Notebooks yet. Tracking of Kaggle Notebooks recommendations started around Nov 2023.

What are some alternatives?

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

Colaboratory - Free Jupyter notebook environment in the cloud.

Microsoft Azure Notebooks - You can enjoy powerful, integrated Jupyter notebooks with the following products and services from Microsoft and GitHub.

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

Deepnote - A collaboration platform for data scientists

DataSource.ai - Community-funded data science tournaments

Noteable.io - Meet Noteable, the collaborative notebook experience that goes beyond silos and breaks down barriers for your data teams.

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