Caveat: multimodal distributions have more than one central or typical value, and they are trickier to describe. If you look at how tall the average adult human is, you will find a bump around 165 cm and another around 175 cm. These local maxima (modes) are useful statistics, but often it pays to prod a little deeper and see why there’s more than one peak in the first place. In the case of human height, the answer is obvious: a typical adult woman is roughly 165 cm tall, a typical adult man roughly 175 cm. Once you split the data by gender, the bimodal distribution disappears.
2016.12.29 | Data Science Newsletter list. [Medium]
2016.12.27 | Sharing Your Side Projects Online and Making Your Github the Best Résumé. [Youtube]
Include a license to the project. there’s even a website that walks you through the copying and pasting process
Binder is a project that allows you to open up the jupyter notebook in a virual environment (specifying all the requirements in a requirements.txt file) and run it online without needing to download it
2016.12.24 | WHAT I LEARNED RECREATING ONE CHART USING 24 TOOLS. [Blog]
The Most Practical Big Data Use Cases Of 2016. [Forbes]
The top 5 habits of a professional data scientist. [OREILLY]
The Inconvenient Truth About Data Science. [Linkedin Pulse]
Data science tips from reddit The Top Five Data Science Tips From r/DataScience. [Blog]
Data scientists mostly just do arithmetic and that’s a good thing. [Blog]
The one machine learning concept you need to know. [Blog]
When you’re doing machine learning (specifically, supervised learning), you’re essentially using computational techniques to find the underlying relationships between the input and the output.
Check Yourself: 5 Things You Should Know About Data Science (Author Note). [Blog]
The questions to ask before implementing any big data strategy. [the guardian]
What is the biggest challenge my business is facing right now and what do you do and don’t know about your customer. and see how you can tweak your current strategy to make it more customer and data-driven.
6 Best Practices for implementing In-store Personalization in 2015. [beaconstac]
Activating purchases: Say, Laura purchased a lemon yellow shirt at your retail store outlet located in New York. Now, a week later, you can send out an offer (via email and through a mobile app push notification) on a brown trouser that’ll go along with the shirt. The offer can be redeemed on your online store or a physical outlet.
Pushing shoppers forward in the buying path: Say the same customer, Laura, actually went on to browse handbags online after she received the email offer. As soon she walks into your physical retail store, you can send a notification through her mobile app, asking if she wishes to touch and feel the handbags that she browsed online.
The top three things that retailers needs to know: how effective their pricing is, when shoppers are most active and what items they buy together (promoting products that shoppers often buy together can boost your average order value and help products move more quickly).
Do data scientists need to be domain experts to deliver good analytics? [Data Science Central]
Often, good data scientists become subject experts just by playing with the data and asking questions to domain experts about the data anomalies. Through their questioning they will cross-pollinate the subject matter experts so the team as a whole is stronger.
Machine learning brings a fresh perspective that leads to new insights and no prior domain knowledge can potentially be advantageous, especially in overcoming long standing domain bias.
Used with Complaints Management, Customer Upsell and Customer Retention. Questions include How to anticipate and manage the dissatisfaction of the customers?‘, ’How to sell more and better to existing customers?’ and ‘How to keep the most profitable customers at an appropriate cost?’
Action: You identify a target behaviour, in our case, it is a specific customer action, like filing a complaint/not filing a complaint, accepting or rejecting an upsell offer, cancelling / not cancelling a service. Then perform supervised learning
Doing Data Science Right — Your Most Common Questions Answered. [Review]
The only way to survive is to build a brand that can grow without Amazon’s distribution.
Amazon hasn’t proven that it can build inspirational brands. While they have mastered the ability to get customers commodity products, no one goes to Amazon to discover something they didn’t already know about.