Jupyter

Welcome to the sixth blog post in our “Kubeflow Fundamentals” series specifically designed for folks brand new to the Kubelfow project. The aim of the series is to walk you through a detailed introduction of Kubeflow, a deep-dive into the various components, add-ons, and how they all come together to deliver a complete MLOps platform. If you missed the previous installments in the “Kubeflow Fundamentals” series, you can find them here: In this post, we’ll focus on getting a little more familiar with Jupyter notebooks and…

TUTORIALMercury provides a simple way to transform Jupyter Notebooks into interactive web apps.Am I referring to code development or CO2 emissions? Photo by Etienne Girardet on UnsplashWhere would we be without Jupyter Notebooks? Surely they are one of the staples of the Data Science community.They are great for prototyping and/or incrementally building and demonstrating a data science application. But they are not so good at presentation.If you want to show your stakeholders the results of your work as a web application,…

Before we can start working on our conversational sessions with ChatGPT, some things need to be done first.OpenAI API key 🔑Since we want to use ChatGPT, we first need a valid OpenAI API key. The needed key can be created under this link and then by clicking on the+ Create new secret key button.OpenAI offers a free trial period before you charge money. The prices are super fair in my opinion, considering that hosting your own LLM is more expensive in many cases.Installing the OpenAI package 📦Once we have the key, we also…

Notebooks to beautiful web apps in no timePhoto by NASA on UnsplashEffective communication is pivotal in all data-driven projects. Data professionals often need to communicate their findings and insights to stakeholders, including business leaders, technical teams, and other data scientists.While traditional methods of communicating data insights, such as PowerPoint presentations and static reports are widely preferred, they are often time-consuming to create.What’s more, these services require one to leave the comfort of…

Deploy machine learning models in one line of codePhoto by Roman Synkevych 🇺🇦 on UnsplashAmidst this AI revolution, building intelligent systems at scale has been of great interest lately to countless organizations.While plenty of time and energy is being actively spent in training large machine learning models, taking these models to production and maintaining them is a task of its own.This, in some cases, may even require specialized teams.And while more and more organizations are resorting to artificial intelligence…

From syntax highlighting to code completion, a complete Python IDE inside JupyterPhoto by Max Duzij on UnsplashThis article is part of a series. Check out the full series: Part I, Part II, Part III.Over the past few days, we’ve been building a complete Python IDE inside Jupyter. In this article, we will add the final touches and package everything in a Docker image to create a portable working environment for data scientists and Machine Learning engineers.Jupyter is not exactly an IDE. It’s not even an IPython UI, as many…

Make Jupyter your all-in-one IDE and elevate your Python development experiencePhoto by Fotis Fotopoulos on UnsplashThis article is part of a series. Check out the full series: Part I, Part II.In previous parts of this series, we covered why many developers do not consider Jupyter as a fully integrated development environment and how the lack of a powerful text editor is one of the main reasons.Thus, we decided to look at JupyterLab as a platform that we could use to create our own Python IDE from scratch. Extending the…

How to get a VS Code-like experience in Jupyter with a great text editorPhoto by Douglas Lopes on UnsplashOur previous article stated that many engineers do not consider JupyterLab a complete IDE. One of the main reasons is that JupyterLab does not have a powerful text editor like VS Code or Sublime Text.JupyterLab allows users to create and share documents that contain live code, equations, visualizations, and narrative text. It’s the perfect tool for this kind of interactive work. However, the truth is that its text…

An Introduction to the PyGWalker Library for Easy Data VisualisationPyGWalker showing multiple plots within the same view. Image by the author.Creating effective and compelling data visualisations quickly and efficiently is a key part of the data science workflow. There are several options available to do this ranging from commercial software like Tableau to free alternatives like dedicated python libraries. The amount of skill and time needed to generate plots can vary between the different options.Over the years,…

With a bonus tipPhoto by Sigmund on UnsplashJupyter Notebook is one of the most sought-after IDEs for almost all Python-oriented programming tasks such as data science, machine learning, scientific computing, and many more.Its interactive coding capabilities make it the go-to tool not only for beginners but experts as well.Yet, despite its widespread usage, many of its users do not use it to its full potential.As a result, they tend to use Jupyter using its default interface/capabilities, which, in my opinion, can be…