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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.

Jupyter Reviews and details

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What is Jupyter Notebook?

Jupyter Notebook Tutorial: Introduction, Setup, and Walkthrough

JupyterLab: The Next Generation Jupyter Web Interface

Social recommendations and mentions

We have tracked the following product recommendations or mentions on various public social media platforms and blogs. They can help you see what people think about Jupyter and what they use it for.
  • Interactive Visualizations of Rate-Limiting Algorithms
    Interesting, I would have guessed you had used something jupyter-like: - Source: Hacker News / 14 days ago
  • scrape-yahoo-finance
    JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: / about 1 month ago
  • Let’s build AI-tools with the help of AI and Typescript!
    Jupyter Lab web-based interactive development environment. - Source: / about 2 months ago
  • Scrape Redfin Property Data
    Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: / about 1 month ago
  • Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
    Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: / 3 months ago
  • Using IPython Jupyter Magic commands to improve the notebook experience
    Note. Nowadays, there are many flavors of notebooks (Jupyter, VSCode, Databricks, etc.), but they’re all built on top of IPython. Therefore, the Magics developed should be reusable across environments. - Source: / 3 months ago
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    They make it easy to launch multiple case-by-case data science projects and run your local code right from Jupyter Notebook. - Source: / 4 months ago
  • MLOps in practice: building and deploying a machine learning app
    Talking to some colleagues and friends lately gathering some ideas of a nice Machine Learning project to build, I’ve seen that there’s a gap of knowledge in terms of how do one exactly uses a Machine Learning model trained? Just imagine yourself building a model to solve some problem, you are probably using Jupyter Notebook to perform some data clean up, perform some normalization and further tests. Then you... - Source: / 5 months ago
  • Stuff I Learned during Hanukkah of Data 2023
    This year I decided to commit to a set of tools on day 1 (Polars and Jupyter) and use them for the whole challenge. It seemed silly to do a whole new meandering walkthrough, so instead I'll highlight a few things that stuck out after finishing the challenge and sitting on it for a few days. Here we go! - Source: / 5 months ago
  • Technical reports generation with Raku
    The resulting technical reports can be in the formats: Markdown, Pod6, or Org-mode. Or just Jupyter notebooks. Source: 7 months ago
  • No comments. Now what?
    Another effective way to use comments is through literate programming. In this programming style, comments take the spotlight: the source code contains more prose than executable code. This is useful when explaining the algorithm is more important than reading it, as in academic research and data analysis. Not surprisingly, it is the paradigm of popular tools like Jupyter Notebook and Quarto. - Source: / 8 months ago
  • Journey into Jupyter Notebooks: A Beginner's Guide
    Imagine sitting in a cozy cafe with your favorite warm beverage in hand. As the rain drizzles outside, I will introduce you to a tool that might revolutionize how you approach code, data, and storytelling. Meet the Jupyter Notebook, an open-source web application tailor-made for interactive computing. - Source: / 8 months ago
  • Learning How to Code?
    Thanks, this is really helpful! I did not know before! - Source: Hacker News / 10 months ago
  • Functional Code Blocks
    Possibly using a similar approach to Jupyter notebooks or lab if not Jupyter itself on top of ipython. Source: 10 months ago
  • No excuses to start working with Python
    Our Jupyter Notebook looks like yesterday I fell in love with this tool, I met in college. I use it to this day. Definition for this tool and simplicity and power. - Source: / 11 months ago
  • How to implement instance segmentation using YOLOv8 neural network
    Let's just start coding. You need an environment when you can run Python code. I recommend to use Jupyter Notebook. In the next sections, all code samples and output assumes that you run this in the Jupyter Notebook. - Source: / 11 months ago
  • Introducing Mercury: The Easiest Way to Share and Deploy Your Notebooks as Web Apps
    You can document your code as you write it. You can include explanations, comments, and visualizations within the same document, making it easier to understand. You can load and manipulate data, visualize it, perform statistical analysis, and generate reports—all in a single notebook. This makes it convenient for exploring and presenting insights from your data. You can find more on e.g. Source: 11 months ago
  • Any Good Alternatives for Matlab?
    Don't forget Jupyter. Allows you to take notes and/ document stuff with in-line python. Source: 12 months ago
  • A Diagramming Software Which Combines Flowcharts And Codes?
    Maybe one of these two things: 1. 2. Source: about 1 year ago
  • Literate Programming: Articles
    I've been experimenting a lot with using Jupyter Notebooks ( to get many features of literate programming. The tooling can be a bit clunky -- though JupyterLab and some plugins can go a long way. Importing notebooks into other notebooks or modules is still kind of weird even with the `ipynb` library. However, on the otherside of it all, you have a collection of documents that contain... - Source: Hacker News / about 1 year ago
  • Why does Python look one way on my laptop and completely different in this video i wanted to watch?
    Jupyter Notebook - popular web browser based editor and run time environment for Python (and R). Source: about 1 year ago

External sources with reviews and comparisons of Jupyter

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Once you install nteract, you can open your notebook without having to launch the Jupyter Notebook or visit the Jupyter Lab. The nteract environment is similar to Jupyter Notebook but with more control and the possibility of extension via libraries like Papermill (notebook parameterization), Scrapbook (saving your notebook’s data and photos), and Bookstore (versioning).
7 best Colab alternatives in 2023
JupyterLab is the next-generation user interface for Project Jupyter. Like Colab, it's an interactive development environment for working with notebooks, code, and data. However, JupyterLab offers more flexibility as it can be self-hosted, enabling users to use their own hardware resources. It also supports extensions for integrating other services, making it a highly customizable and versatile tool for data...
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Jupyter Notebook is a widely popular tool for data scientists to work on data science projects. This article reviews the top 12 alternatives to Jupyter Notebook that offer additional features and capabilities.
15 data science tools to consider using in 2021
Jupyter Notebook's roots are in the programming language Python -- it originally was part of the IPython interactive toolkit open source project before being split off in 2014. The loose combination of Julia, Python and R gave Jupyter its name; along with supporting those three languages, Jupyter has modular kernels for dozens of others.
Top 4 Python and Data Science IDEs for 2021 and Beyond
Yep — it’s the most popular IDE among data scientists. Jupyter Notebooks made interactivity a thing, and Jupyter Lab took the user experience to the next level. It’s a minimalistic IDE that does the essentials out of the box and provides options and hacks for more advanced use.
The Best ML Notebooks And Infrastructure Tools For Data Scientists
Jupyter Notebook is an open-source platform that supports more than 40 programming languages, including R and Python. ipynb, the default format for Jupyter files, is a JSON file and can be easily version controlled and shared using email, Dropbox, Github, and Jupyter Notebook Viewer. Jupyter Notebook supports big data integration through Apache Spark, a top analytics engine for in-memory data processing. The...
Top 5 Python IDEs For Data Science
1071070Related postsmust readpython+2Jupyter Notebook Tutorial: The Definitive GuideKarlijn WillemsJanuary 9th, 2019machine learning+2Deep Learning With Jupyter Notebooks In The CloudDan BeckerMarch 23rd, 2017learning data science+2AWS EC2 Tutorial For BeginnersMichael GalarnykDecember 6th, 2017Post a CommentSubscribe to RSSAboutTermsPrivacyWant to leave a comment?...

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