News clips about JupyterHub, JupyterLab, and Jupyter Notebooks provided algorithmically.
How to Deploy JupyterHub with Kubernetes on OpenStack
Deploying JupyterHub with Kubernetes on OpenStack
Jupyter is now widely used for teaching and research. The use of Kubernetes for deploying a JupyterHub has enabled reliable setups scaling to thousands of users.
There are many cloud computing vendors (Google, Amazon, …) and the first attempts to use JupyterHub with Kubernetes is based on them. But relying on vendor clouds increases the risk of vendor lock-in.
In addition, there are many pre-ex…
2018-10-15 13:11:34.092000+00:00 Read the full story.
How to Export Jupyter Notebooks into Other Formats
When working with Jupyter Notebook, you will find yourself needing to distribute your Notebook as something other than a Notebook file. The most likely reason is that you want to share the content of your Notebook to non-technical users that don’t want to install Python or the other dependencies necessary to use your Notebook. The most popular solution for exporting your Notebook into other formats is the built-in nbconvert tool. You can use nbco…
2018-10-09 00:00:00 Read the full story.
Testing Jupyter Notebooks
The more you do programming, the more you will here about how you should test your code. You will hear about things like Extreme Programming and Test Driven Development (TDD). These are great ways to create quality code. But how does testing fit in with Jupyter? Frankly, it really doesn’t. If you want to test your code properly, you should write your code outside of Jupyter and import it into cells if you need to. This allows you to use Python’s …
2018-10-16 00:00:00 Read the full story.
Predicting the Stock Market Using Machine Learning and Deep Learning
Predicting how the stock market will perform is one of the most difficult things to do. There are so many factors involved in the prediction – physical factors vs. physhological, rational and irrational behaviour, etc. All these aspects combine to make share prices volatile and very difficult to predict with a high degree of accuracy.
Can we use machine learning as a game changer in this domain? Using features like the latest annou…
2018-10-25 08:38:44+05:30 Read the full story.
Google’s New Machine Learning Curriculum Aims to Stop Bias Cold
Google loves machine learning (ML). Now, it’s launched a new course module that aims to help you, a human, recognize your own bias before training ML models.
Named ‘Fairness,’ the course is 70 minutes on how humans are compromising machine learning models. From Google:
As ML practitioners build, evaluate, and deploy machine learning models, they should keep fairness considerations (such as how different demographics of people will be affected b…
2018-10-24 00:00:00 Read the full story.
Airbnb details its journey to AI-powered search
Online booking platform Airbnb has more than 5 million property listings and tens of thousands of tours, hikes, and other travel experiences on offer. That’s a lot for anyone to sift through, but the San Francisco startup believes that artificial intelligence (AI) can lend a hand.
In a paper published on the preprint server Arxiv.org (“Applying Deep Learning To Airbnb Search“), researchers at the company describe how over the course of two years…
2018-10-24 00:00:00 Read the full story.
Azure Content Spotlight – Get started with developing AI applications
Welcome to another Azure Content Spotlight! These articles are used to highlight items in Azure that could be more visible to the Azure community.
This weeks content spotlight is all for developers that want to get started with developing AI applications or more experienced AI developers that want expand their knowledge.
AI is a set of technologies that enable computers to assist and solve problems in a way that are similar to humans by perceiv…
2018-10-25 00:00:00 Read the full story.
PyDev of the Week: Marc Garcia
This week we welcome Marc Garcia (@datapythonista) as our PyDev of the Week! Marc is a core developer of pandas, a Python data analysis library. If you’d like to know more about Marc, you can check out his website which has links to his talks that he has given at PyData in Europe as well as talks at EuroPython.
In fact, here is one of his talks on pandas in case you are interested:
You can also see what projects he is a part of over on Github. …
2018-10-15 00:00:00 Read the full story.
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