Using ObservableHq Online (Notebook) Editor For JavaScript ML Programming Like Python Jupyter Notebook

 

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Observable is not just another JavaScript sandbox. It introduces the notebook paradigm to JavaScript projects, those of you familiar with Jupyter notebooks, this is the equivalent with JavaScript instead of Python. It turns out JavaScript is very well-suited to this type of paradigm.

What’s more, JavaScript developers already have some sort of familiarity with reactivity since most frontend frameworks and view libraries build on it. It’s a different kind of reactivity, in that the library only re-renders or re-computes the section of the application that needs it (cf. Vue, Angular, React).

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https://codewithhugo.com/observablehq-notebooks-for-javascript-demos-and-prototypes/

ObservableHq Tutorial: An Interactive Introduction to TensorFlow.js

 

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1) Import the TensorFlow.js

2) Import A helper method to show the tensor array

3) Create a model that is used to predict the MNIST dataset. The module constitutes two conv layers two pooling layers and a dense layer. Compile the model using an adam optimizer.

4) Load a pretrained model called mobilenet.

5) Load the image classes.

6) Predict image class.

6.1) Preprocess the image by converting it to a tensor then normalize,

6.2) Predict based on the given model classes

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https://observablehq.com/@zaidalyafeai/an-intractive-introduction-to-tensorflow-js

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Alternative:

https://observablehq.com/d/95a9b4e931cccfb0

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ObservableHq Tutorial: Introduction to Data (JavaScript ML Notebook Alternative To Python ML Jupyter Notebook)

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Introduction to Data

How do you get data into Observable for analysis and visualization? Depending on its form and where it lives, there are a variety of ways:

• inline - embedded in the notebook as code, for small amounts of data
• files - attached to the notebook, for medium amounts of data (e.g., CSV, SQLite)
• APIs - queried from a remote server, for programmatic access to data
• databases - via an Observable database client, for accessing SQL databases

You can also download generated data from notebooks.

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https://observablehq.com/@observablehq/introduction-to-data

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SQLite

Observable has built-in support for SQLite, “a small, fast, self-contained, high-reliability, full-featured, SQL database engine” and “the most used database engine in the world.” Observable’s SQLite client uses sql.js, an Emscripten port of SQLite.

After attaching a SQLite file to your notebook, create a SQLite database client by calling file.sqlite().

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https://observablehq.com/@observablehq/sqlite

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