Issue 138
— Notes —
Thanks to everyone who participated in last week's "What are you reading" survey. Responses are still coming in. I'll post a top-10 list here next week.
— In the News —
In a few years, no investors are going to be looking for AI startups
It won't be long before investors stop looking for AI powered startups in the same way they don't look for startups that use databases. AI will just be assumed.
— Sponsored Link —
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— Tools and Techniques —
The data engineering ecosystem in 2017
Great overview of the current data engineering ecosystem. The article discusses industry trends and the accompanying interactive offers an easy way to explore the options. This is definitely worth bookmarking.
Learning from Real-World Models: The Mississippi Basin Model and Machine Learning
It's easy to forget that modeling has been around for a long time. This article explores how real-world models from the past relate to machine learning models today.
Web Scraping with Python and BeautifulSoup
Nice tutorial for extracting data from a web page. Starts with the basics of understanding the structure of a page and uses movie recommendation sites to show how to parse, extract, and analyze a site's data.
How to build a data science pipeline
This is a high-level, executive perspective of things to think about when designing your infrastructure. Along with being useful for decision-makers, this big-picture view will help data scientists and engineers understand the thinking behind the systems they're working with.
— Resources —
A gallery of interesting Jupyter Notebooks
Great collection of curated Jupyter notebooks covering a wide variety of topics including things like statistics, programming, signal processing, data visualization, math, natural language processing, scientific computing, etc.
Medical Data for Machine Learning
This curated collection of medical-related datasets offers a lot of possibilities for building machine learning applications. There are a wide variety of datasets here, including imaging data (such as brain scans and retinal images), data derived from Electronic Health Records, data about diseases, etc.
— Deep Learning —
How HBO’s Silicon Valley built “Not Hotdog” with mobile TensorFlow, Keras & React Native
Here's the official version the of the hotdog / not-hotdog app that was recently featured on an episode of Silicon Valley. Yes, the HBO Show actually built this app. This is a fantastic tutorial that includes the thinking behind the app, architecture, training details, insights about running neural nets on mobile phones, UX decisions, lessons learned, etc.
— Data Viz —
Data Visualization Pitfalls to Avoid
This is a dense and insightful slide deck by Tamara Munzner. Tamara is well-known in the visualization community. She's published over sixty-five papers and her book, Visualization Analysis and Design, appeared in 2014.
— About —
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