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Colaboratory VS Data Scientist Workbench by IBM

Compare Colaboratory VS Data Scientist Workbench by IBM and see what are their differences

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Colaboratory logo Colaboratory

Free Jupyter notebook environment in the cloud.

Data Scientist Workbench by IBM logo Data Scientist Workbench by IBM

Making open source data science easy
  • Colaboratory Landing page
    Landing page //
    2022-11-01
  • Data Scientist Workbench by IBM Landing page
    Landing page //
    2023-02-01

Colaboratory features and specs

  • Free Access
    Colaboratory is freely available to anyone with a Google account, making it accessible for students, researchers, and developers without cost barriers.
  • Cloud-based
    Colab operates in the cloud, eliminating the need for local computational resources and allowing access from any device with internet connectivity.
  • GPU and TPU Support
    Colab provides free access to GPUs and TPUs, which can significantly speed up machine learning tasks and deep learning experiments.
  • Integration with Google Drive
    Easy integration with Google Drive allows for convenient storage and retrieval of data, notebooks, and other resources.
  • Collaborative Editing
    Multiple users can collaborate on a notebook in real-time, making it a valuable tool for team projects and pair programming.
  • Pre-configured Environment
    Colab comes pre-installed with a wide array of popular machine learning libraries and dependencies, reducing setup time and effort.

Possible disadvantages of Colaboratory

  • Session Time Limits
    Colab has time limits for sessions, meaning your environment can be reset if left idle for too long or if the maximum session duration is reached.
  • Resource Limits
    There are limitations on the computational resources and memory available, which can be restrictive for very large and complex tasks.
  • Dependency Management
    While many libraries are pre-installed, managing and updating dependencies can sometimes be problematic, leading to conflicts or version issues.
  • Privacy Concerns
    Since your code and data are stored on Google’s servers, there can be privacy and security concerns related to sensitive information.
  • Network Dependency
    Being a cloud-based service, Colaboratory requires a constant internet connection, which may not be feasible in all scenarios or locations.
  • Limited Customization
    Customization of the environment is limited compared to a local setup where you have full control over system configurations and installed software.

Data Scientist Workbench by IBM features and specs

No features have been listed yet.

Colaboratory videos

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Google Colaboratory review: the best tool for Python programming and data analysis

Data Scientist Workbench by IBM videos

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Category Popularity

0-100% (relative to Colaboratory and Data Scientist Workbench by IBM)

Colaboratory

Data Scientist Workbench by IBM

Development
100 100%
Development
0% 0
AI
0 0%
AI
100% 100
Online Learning
100 100%
Online Learning
0% 0
Developer Tools
0 0%
Developer 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 Colaboratory and Data Scientist Workbench by IBM

Colaboratory Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Google Colaboratory (known as Colab) is a browser-based notebook created by the Google team. The environment is based on the Jupyter Notebook environment, so it will be recognizable to those of you who are already familiar with Jupyter.
Source: lakefs.io
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Microsoft Azure Notebooks is a cloud-based platform for data science projects and machine learning that is similar to Google Colab and Kaggle Notebooks. It provides access to powerful hardware resources, including GPUs and TPUs, for running machine learning and deep learning models, as well as a number of other useful features, such as integration with Microsoft Azure...
Source: noteable.io

Data Scientist Workbench by IBM Reviews

We have no reviews of Data Scientist Workbench by IBM yet.
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Social recommendations and mentions

Based on our record, Colaboratory seems to be more popular. It has been mentiond 224 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.

Colaboratory mentions (224)

  • Introduction to TensorFlow with real code examples
    If you don't want to set up TensorFlow locally, you can use Google Colab, which comes with a GPU by default. You can access it via this link. - Source: dev.to / about 1 month ago
  • The 3 Best Python Frameworks To Build UIs for AI Apps
    Showcase and share: Easily embed UIs in Jupyter Notebook, Google Colab or share them on Hugging Face using a public link. - Source: dev.to / about 2 months ago
  • Build a RAG-Powered Research Paper Assistant
    Google Colab Documentation Beginner-friendly documentation to get started with Google Colab: Https://colab.research.google.com/. - Source: dev.to / 2 months ago
  • PyTorch Fundamentals: A Beginner-Friendly Guide
    If you don't want to install PyTorch locally, you can use Google Colab, which provides a free cloud-based environment with PyTorch pre-installed. This allows you to run PyTorch code without any setup on your local machine. Simply go to Google Colab and create a new notebook. - Source: dev.to / 3 months ago
  • Applied Artificial Intelligence & its role in an AGI World
    Leverage versatile resources to prototype and refine your ideas, such as Jupyter Notebooks for rapid iterations, Google Colabs for cloud-based experimentation, OpenAI’s API Playground for testing and fine-tuning prompts, and Anthropic's Prompt Engineering Library for inspiration and guidance on advanced prompting techniques. For frontend experimentation, tools like v0 are invaluable, providing a seamless way to... - Source: dev.to / 4 months ago
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Data Scientist Workbench by IBM mentions (0)

We have not tracked any mentions of Data Scientist Workbench by IBM yet. Tracking of Data Scientist Workbench by IBM recommendations started around Mar 2021.

What are some alternatives?

When comparing Colaboratory and Data Scientist Workbench by IBM, you can also consider the following products

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Gyana - Intuitive easy-to-use report and dashboard tool to stop wasting time on repetitive and tedious tasks.

Kaggle - Kaggle offers innovative business results and solutions to companies.

Deepnote - A collaboration platform for data scientists

Teammately.ai - Teammately is The AI AI-Engineer - the AI Agent for AI Engineers that autonomously builds AI Products, Models and Agents based on LLM, prompt, RAG and ML.

Data Science & it's Essentials - Must haves for a Data Scientist

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