Software Alternatives & Reviews

The Best ML Notebooks And Infrastructure Tools For Data Scientists

Recommended and mentioned products

  1. 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.

    How To Start Learning Data Analysis, Step By Step Guide about 10 days ago:

    Jupyter Notebook system: It makes testing, sharing, and creating life documents, codes, and text easy. Because of its markdown functionality, jupyter notebooks are more popular with non-technical folks.
  2. Kaggle offers innovative business results and solutions to companies.

    What online course should I study next? about about 1 month ago

    In my opinion, stop the learning loop and create simple to complex projects. During development kasi ng mga projects, may maeencounter ka pa na new knowledge as alam mo currently. When I'm still pursuing Data Analytics before (I'm a dev now btw), nagte-take ako ng mga challenges sa kaggle then nag c-create din ako ng analytics from the available datasets sa kaggle as practice and to hone my skills further. Also,...
  3. Free Jupyter notebook environment in the cloud.

    Cheapest CUDA-Compatible Cloud GPU Options in 2023 about 3 days ago:

    Is there a cheaper option? Yes, there is. You could use Google Colab, which offers a 16GB T4 GPU for free, but with the drawback of having to periodically respond to human verifications.
  4. As a free css gradient generator tool, this website lets you create a colorful gradient background for your website, blog, or social media profile.

    Linear Gradient bug, the top and bottom line seem to be... about 9 days ago

    FYI this is a javascript sub. But use this tool to create your gradient: https://cssgradient.io/.
  5. A collaboration platform for data scientists

    Quick tip: Using a SingleStoreDB Recursive CTE with London... about 15 days ago

    Using Deepnote, we'll create a Python notebook and upload the two GeoJSON files into a data directory.
  6. A data science & machine learning platform for scalable Python with Dask & GPUs. GPU-accelerated data science. Join for free.

    free-for.dev about 3 months ago:

    SaturnCloud - Data science cloud environment, that allows to run Jupyter notebooks and Dask clusters. 30 hours free computation and 3 hours of Dask per month.
  7. A web-based notebook that enables interactive data analytics.

    Visualization using Pyspark Dataframe about 9 months ago:

    Have you tried Apache Zepellin I remember that you can pretty print spark dataframes directly on it with z.show(df).
  8. The polyglot notebook with first-class Scala support.