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Downloading a Video from Facebook

Hey... here's a neat trick for downloading a video from Facebook:


First, notice that your "Saved videos" can usually be found in the upper right menu (where birthdays usually show up) or under the "Saved" button in the left menu.




Once you click on the saved video, you'll find the file... click on that bad boy to play it in the browser.




Once it's playing, notice that there's no way to download it (that's what we're gonna "hack")





In the URL of the playing video, replace www with m (for mobile)





You should be brought to the funky looking mobile site (even though you're on a regular browser)





Play the video and then right click, you should see the following menu:





Save it as an MP4, crack a beer, and enjoy your Video whenever you want without having Facebook open.


Recent posts

Big Data as Big Brother

Yesterday and today, it seems like one of the biggest news items is the Big Data of Big Brother. 

The argument goes like this:

The U.S. government is aggregating the same kind of social media and online user data that private companies use to understand their customers' sentiments (or potential customers) for the express purpose of counter terrorism, reporting on potential defense threats, and generally trying to figure out who the "bad guys" in the world are...

Using data from companies such as Apple, Google, Facebook, Microsoft, Skype, Yahoo, YouTube, and others, the National Security Agency is able to obtain all types of data (1). Now, when one considers the total size of this data it's clear to see that this exits the world of statistical analysis and enters the world of Data Science and Big Data. 

To give you an idea of the size of the data, "The amount of data in question is enormous. For example, the U.S. wireless-communications trade association C.T.I.A. est…

The life stats have waned... but there is this. . .

My last few weeks with a newborn have been trying to the point that tracking life stats hasn't been too feasible..But, for now, I want to talk about some articles I found while searching around for Data Science news:

First, from the Star Tribune, Minnesota Companies and Workers Cache in on Big Data, a quick word cloud shows words such as: Oracle, information, data, and software; however, it's the words like Hadoop, and Data Science that stand out to me. It's an exciting time for the field of Data Science. 


One encouraging quote from the article really makes me excited about the field:


'I would challenge you to describe to me an organization of any size in any industry or not-for-profit setting that will not be leveraging [Big Data],' said Isaac Cheifetz, a headhunter working to find the Mayo Clinic a head of information management and analytics. 'Name one. I can’t'"

What this tells me is that there is going to be rising demand for people with the skills t…

Life Statistics

Today I used Excel to analyze total email volume and client specific email volume data (sent/received) weighted by an "effort" ranking to help highlight work flow at the office. In the interest of not having to check my email as much as I am currently, I hoped to shed light on prioritization of time spent with email vs projects. 


My hope is to only check my email twice a day... But, given the client service that my role entails, that's probably not gonna happen. One thing that came out of my analysis though is when getting the most email (day of week/time of day) is most probable. It turns out Tuesday mornings and Friday afternoons are the most likely times for stuff to hit the proverbial "fan."


In other life statistics news (and productivity measures), I'm tracking my time spent during the day in a manner similar to the "hyper tracking" concept I've learned from listening to The Better Guy Show podcasts (available on iTunes). In the next week I…

Data Science Course (Complaint # 2?)

Looks like I'm not the only one having problems with the first assignment for UW's Introduction to Data Science.... while Professor Howe has certainly whetted my appetite for wanting to learn more useful DS than I've learned before, the first assignment seems like a weed-out assignment. I remember from my economics days that this is actually a fairly common practice among econometricians (thanks Professor Levy). [Side note: I'm STILL working my way through Data Analysis and Regression: A Second Course in Statistics.]

I've submitted most of what was required in a Python file for A1P2; however, it's probably going to get a 0/10. I fully intend on sticking with this course after reading a lot of the complaints. Most of the people complaining seem to have the "must have now" mentality; fortunately my years of dealing with this kind of stuff is that it rarely comes easy... that said, my intent to blog along with this course is going to be less sporadic and …

python stuff

I'm realizing that some of my difficulty is directly related to my rustiness with Python. The problem I am dealing with right now has to do with reading files into Python and parsing them. The data type that Twitter's APIs come in are of the "dict" variety... Now, when I read the data into Python from the Twitter live stream sample (as saved into a text file), I loose the ability to choose the appropriate key...

i'm gonna keep working at it.. but it's definitely frustrating. I'm not going to get this assignment in on time--that's for sure.

-Anton

Get Git

The requirements for the data science class that I'm taking include having access to R, Python, SQL and GitHub. As I'm already familiar with R, Python, and SQL, my goal tonight was to get started with GitHub. According to Wikipedia, "GitHub is a web-based hosting service for software development projects that use theGitrevision control system. GitHub offers both paid plans for private repositories, and free accounts for open source projects. As of May 2011, GitHub was the most popular open source code repository site.[3]"

So, basically people come together on this website and share code... if you don't want to pay, you agree to have your code (in your "repository") available as open source. The future is Crowd Sourcing...


and speaking of the future, I think this chart from the GitHub website is an interesting reference for those looking to figure out what programming languages they should be working on if they want to remain competitive in the future:



Obvi…