Issue 8
Intercom Analytics: How to build a dashboard for Customer Success
Customer success isn’t easy. It costs time and money. But putting your customers front and measuring your efforts pays off. Lincoln Murphy said “Customer success is when your customers achieve their desired outcome through their interactions with your company.” Let’s explore how to track Customer Success.
Data Analysis
Curtis Miller wrote one of the most shared articles this week. He made an intro to stock market analysis with Python. How to get stock data with pandas, visualize and analyze it. This is “An Introduction to Stock Market Data Analysis with Python (Part 1)” and “An Introduction to Stock Market Data Analysis with Python (Part 2)”
Data Science, Machine Learning, AI
Eric Siegel author and founder of the Predictive Analytics World conference series (among others) explores how (and if) Hillary’s campaign is using Big Data and a highly targeted technique that worked for Obama in “How Hillary’s Campaign Is (Almost Certainly) Using Big Data” via Sientific American.
Nate Cohn writer for The New York Times discusses “margin of sampling error” and how two good pollsters, both looking at the same underlying data, could come up with two very different results. He made an experiment with four! Read the details in “We Gave Four Good Pollsters the Same Raw Data. They Had Four Different Results” via The New York Times.
Matthew Mayo, Deputy Editor of KDnuggets highlights a new update to Conway’s classic Data Science-related Venn diagram in “The (Not So) New Data Scientist Venn Diagram” via KDnuggets.
Dr. Deepak Chopra that The Huffington Post global ranked him as #40 influential thinker in the world, examines if and how AI technology can actually rival humans in “Artificial Intelligence Will Never Rival the Deep Complexity of the Human Mind” via Huffington Post.
Data architecture
Dean Wampler, Big Data Architect at Lightbend, talks in this podcast about streaming data applications, Scala and Spark, and cloud computing. Hear the podcast
Resources
Google Trends Datastore, is a store with datasets from Google Trends. It is being curated by the News Lab at Google. Get the Google Trends Datastore from here.
Learning statistics on Youtube. A great list!
Good Reads
Building Slack Bots! An awesome tutorial in Python on Building PokéSlacker: The Slack Bot from insightdatascience.com
Lukas Biewald of CrowdFlower wrote a great post on “How to build a robot that “sees” with $100 and TensorFlow” via O’Reilly.
If you build too many bots though they may fight. Here is the proof “The Growing Problem of Bots That Fight Online” and here is the relevant paper published by Milena Tsvetkova, Ruth García-Gavilanes, Luciano Floridi, Taha Yasseri
Visdown, Make visualisations using only markdown! See Visdown here. Nice…
