In the News
How To Call B.S. On Big Data: A Practical Guide
The problem with big data is its apparent sophistication and precision can effectively disguise a great deal of bullshit...
If Your Company Isn’t Good at Analytics, It’s Not Ready for AI
The Harvard Business Review has been taking a hard look at the practical side of AI for businesses recently. This latest article explores the capabilities that should already be in place before thinking about adding AI. Like it or not, you shouldn't ignore the basics.
Sponsored Link
Using Python pre-bundled for machine learning and data science
Python is the ideal language for data science, but getting set up with all the libraries you need can be time-consuming. ActivePython is pre-bundled with over 300 packages including NumPy, SciPy, scikit-learn, TensorFlow, Theano and Keras, and is integrated with the Intel Math Kernel Library (MKL) for optimized NumPy and SciPy computations. It’s free to use in development, so you can get started in minutes.
Tools and Techniques
Python For Finance: Algorithmic Trading
Nice introduction to picking stocks with Python. Starts with an overview of what financial data looks like, common tools, ways to analyze the data, and some basic strategies.
Visualize data instantly with machine learning in Google Sheets
Google just released a new feature to their free spreadsheet product that enables users to simply ask questions of their data using natural language. For instance, you can ask “what is the distribution of products sold?” or “what are average sales on Sundays?” and Explore will help you find the answers.
Google Brain Residency
Ryan Dahl is a very accomplished software engineer who got to spend a year in the Google Brain Residency Program. In this post, Ryan takes a look at some of the projects he worked on and describes what it's like to dive into machine learning from an engineering perspective. His Thoughts and Conclusions section, especially, is gold.
Hands-On Machine Learning - Jupyter Notebook Collection
This series of Jupyter notebooks walks through the fundamentals of Machine Learning and Deep Learning using Scikit-Learn and TensorFlow. It contains the example code and solutions to the exercises in the new book, Hands-on Machine Learning with Scikit-Learn and TensorFlow.
Projects
Crowdsourcing Data Analysis
Great idea. In this crowdsourced analytics project, many teams will analyze the same data and then compare the code and results. In this phase, they're trying to pinpoint exactly why analytic choices have such a profound effect on research results. This Google Doc offers details and instructions for getting involved.
Deep Learning
The Strange Loop in Deep Learning
Loops aren't typical in Deep Learning systems but researchers are discovering that loops are creating mind-boggling capabilities for automation. This overview explores how loops work in a variety of network architectures and why "strange loops" are the fundamental reason for what Yann LeCun describes as the coolest idea in machine learning in the last twenty years.
You can probably use deep learning even if your data isn't that big
Jeff Leek started a popular conversation on Twitter a couple weeks ago with his post, Don’t use deep learning your data isn’t that big. This post by Andrew Beam considers a simple counter-example and reasons why deep learning works in practice.
Data Viz
iD3 - an Integrated Development Environment for D3.js
iD3 is an open-source, cross-platform desktop application that's designed to make it easier to create data visualizations using D3. The intention here is to make D3 useful for people who aren't necessarily JavaScript pros.
Data Elixir is curated and maintained by @lonriesberg. For additional finds from around the web, follow Data Elixir's social media accounts on Twitter, Facebook, and Google Plus