Previously I mentioned that online statistics learning resources are not abundant.
Well, here is a new online book for learning statistics. It is geared towards programmers, and it looks to be a great fit for people wanting to learn data science. Here is a small excerpt from the Preface:
It emphasizes the use of statistics to explore large datasets.
I have only had time to quickly browse the book, but it looks quite good.
Think Stats: Probability and Statistics for Programmers
(The book has a Creative Commons license, so it is free and OK to download)
The Coursera Probabilistic Graphical Models course officially starts today. Sign up and start learning.
The tag line for Kaggle is “We’re making data science a sport.” They have successfully created a way to turn data science into a competition. It is both fun, and it yields excellent results. There is also a portion of the site dedicated for classroom use. It is called Kaggle in Class.
Here is how it works. A company that needs some data analyzed can contact Kaggle and host a competition. Then data scientists all over the world can compete to find the best solution. The company benefits from having many algorithms and techniques applied to the same data set. Many more algorithms are applied than what the company could run without Kaggle. The contestants benefit from networking, pre-cleaned data, and learning from others. It is a win/win situation. Plus, the winner gets prize money.
Currently, the large featured competition is the Heritage Health Prize. It is a $3,000,000 competition to identify individuals that will be admitted to the hospital in the next year. The contest lasts until April 2013.
This is definitely a site I want to be involved with in the future. I just wish they could make it a spectator sport as well.
Data Scientist is the hot new job for 2012. Does this job really exist? Who hires these people? Are companies currently hiring? The answers are: yes, lots of companies, and yes. I decided to spend last night looking for companies that are currently hiring data scientists. It did not take long to compile a pretty good list.
Data Scientist Job Openings
||Microsoft Sr. Data Scientist
||Los Gatos, CA
||NetFlix Senior Data Scientist
||San Francisco, CA
||Kaggle Data Scientist
||San Mateo, CA
||Greenplum Data Scientist
||Last.fm Data Scientist
||San Antonio, TX
||Rackspace Data Scientist
||Amazon Data Scientist/System Architect
||Menlo Park, CA
||Facebook Data Scientist
||San Francisco, CA
||Twitter Data Scientist
||Mountain View, CA
||LinkedIn Data Scientist
||Cobalt Data Scientist
||San Jose, CA
||Paypal Data Scientist
||San Jose, CA
||Bunchball Data Scientist
||Palo Alto, CA
||Principal Engineer/Data Scientist
||Little Rock, AR
||Acxiom Data Scientist
||San Francisco, CA
||Trulia Data Scientist – Data Science Lab
Do you know of any other companies hiring Data Scientists right now?
Statistics – This is a topic that could use some more attention from the online community.
I would love to see Stanford (or Coursera) offer a free statistics course online much like the other free courses online.
I did find a series of Youtube videos by Daniel Judge, a Professor in the East Los Angeles College Mathematics Department. The videos start at the very beginning of statistics. I have watched a couple of the videos, and they seem quite good. Daniel does a nice job of explaining the information. Here is the first video in the series.
Stay tuned to the blog in case other stats options appear online. Also, please leave a comment if you know of some good online statistics resources.
Jeremy Howard is the Chief Scientist at Kaggle. At the end of this interview, from the Strata Conference 2012, he identified 4 simple traits that a data scientist needs.
- A Good Skillset
Jeremy Howard of Kaggle at Strata 2012
In this brief interview he covers a range of other data science topics:
- Big Data is an engineering problem
- Analytics generate value/insight from data
- Predictive Modeling is about answering a question – build a model to do that
- Is Data Science about tools or people? – watch the video for Jeremy’s answer
- And others…
See this previous post for more videos from Strata 2012.
Last week, Heroku announced a new feature to its PostgreSQL database service. The new feature is called Data Clip, and it allows users to share results of an SQL query. It has options to store the exact data from when the query was originally run or the query can be refreshed to return the current data. I can definitely see this being useful for debugging of code and troubleshooting, which may have been Heroku’s original intent.
I can also see the Data Clip being very useful for data science and quick sharing of relevant data. I doubt the Data clip can handle huge result sets, but huge data is not always necessary. Sometimes, being able to quickly share data results is just as important. Plus the Data Clip allows the results to be downloaded into Excel, csv, json, or yaml formats. Therefore the data can be easily manipulated from there.
See an example in action.
If I am going to create a blog about becoming a data scientist, I must at least provide some type of definition. One of the best definitions I have read is by Hilary Mason, Chief Scientist at Bit.ly,
A data scientist is someone who can obtain, scrub, explore, model and interpret data, blending hacking, statistics, and machine learning.
This definition is short and simple, but there are many more definitions out there. In fact CITO Research, a site for CIOs and CTOs, set out to define what a data scientist is. They interviewed six leaders in the data science community, and posted all of the interviews online. The interviews produced varied results, but focused on some main themes of what a data scientist should know.
After reading Hilary’s definition, the CITO Research interview’s, a great post at Quora, and numerous other articles, I created a list of data science skills:
- Machine Learning
- Story Telling (Communication)
- Big Data
I am sure this list will change and evolve over time, but that is where I am going to focus for now. If you have anything to add to the list, please leave a comment. If you are interested in gaining some data science skills, please follow along and let’s learn together.
Obviously the world does not need another blog. However, blogs are a great way to share information, and I am creating a new one anyway.
The analysis of data is becoming more important everyday. Data Science is quickly becoming a hot topic of interest, and I have a desire to become a data scientist. Thus, this blog will contain information I find useful during my data science journey. I hope others find the blog useful too.
If you are interested in becoming a data scientist, please follow along and let’s start learning together.