Exploring the Lyft Prediction Dataset with a novel visualization toolkit .Autonomous Driving Dataset Visualization with Python and VizViewer
I am going to list magic commands in Jupyter Notebook that are used most often and show practical examples of how to take an advantage of the functionality they provide. Boost your productivity by learning the most useful commands.
For a lot of data scientists, notebooks are the only way they have learned to write code. Though Jupyter Notebook has well-known defaults, there is no better Python tool actually for exploratory analysis and quick tests. The point is that you are probably lacking something if most of your work relies on Jupyter Notebook.
This Jupyter Notebook tutorial aims to help you see the big picture of what you can do with Jupyter Notebooks and empower you to maximaThis tutorial on getting started with Jupyter Notebook aims to help you see the big picture of what you can do with Jupyter Notebooks and hopefully, empower you to maximize your efficiency as a Data Scientist.ize your efficiency.
Testing Data-driven Microservices. When it comes to testing microservices, the level of complexity is raised up a notch. Microservices architecture requires the data to be passed around between components (MQ, DataBase…), which can cause erosion and damages that are hard to detect
Convert Your Jupyter-notebook to Github pages with Github-action. Merge pull request and wait until Github-action makes Github pages.
Deploy a Machine Learning Model from a Jupyter Notebook. To do this we will use Watson Machine Learning, and a Jupyter Notebook. I will assume you already have Anaconda or another environment that can run notebooks.
Data scientists do lots of exploration and experimentation. Jupyter Notebook (Notebook from here onwards) is a great tool for exploring and experimenting. However, things can get cluttered and messy quickly when using Notebook.
In this article, I am explaining how to access the Jupyter notebook in AWS EC2 instance directly through a Docker image. No need to install Anaconda or Jupyter in the AWS EC2 instance.
Jupyter Notebook provides a great platform to produce human-readable documents containing code, equations, analysis, and their descriptions. Some even consider it a powerful development when combining it with NBDev.
Why switch to JupyterLab from jupyter-notebook? Jupyter Notebook is a web-based interactive computational environment for creating Jupyter notebook documents.
I want to create an interface that presents information relevant to my 401k investment in one place instead of having to switch between different platforms.
Jupyter and Markdown. Whether you are sharing your Jupyter Notebooks with friends and colleagues or publishing them more widely, they will be better appreciated if they are well laid out and formatted.
How to use tortus annotation tool. This was the inspiration behind building tortus, a tool that makes it easy to label your text data within a Jupyter Notebook!
The Key to Sharp Matplotlib Graphs with One Line of Code. The barely known trick that should become industry standard
The easiest and fastest way to make GIFs and math videos with Python. How to create amazing animations in seconds using Celluloid.
Could Pluto Be A Real Jupyter Replacement? A brief overview and comparison between Pluto.jl notebooks and other development solutions for the Julia programming language.
Multiple Linear Regression model using Python: Machine Learning. Learning how to build a basic multiple linear regression model in machine learning using Jupyter notebook in python
If you have an iPad and want to use it as a development tool, you only need to complete 5 steps before using it. In this guide, you'll learn how to: Set up an instance in a cloud; Purchase ssh client; Set up ssh ; Connect to the serve.
No more Python env and package update. In this article, you will learn how to run Jupyter on Docker.