Data Artistry: Using and Sharing the Knowledge in an Effective Manner
“Can you picture that?” – Dr. Teeth and The Electric Mayhem
The final stage of doing data science/machine learning/data mining/predictive analytics is to use the results, which generally involves some form of communication to one or more types of audiences. This, I will term “data artistry”. (This is not necessarily a common term used, but it does have some precedence in specific contexts)
Data Mining: Discovering Gold in your Data
“There’s gold in dem dere data!” – Adaptation of the original quote from M. F. Stephenson
After the data has been gathered and in a form that can be used, it can then have an appropriate algorithm used to accomplish the data mining/machine learning/predictive analytics. This is the stage that traditionally has been called “data mining” because it is the part that gets additional value from the data in the form of some type of knowledge (this is why early on, the process was sometimes called “knowledge discovery in data” (KDD).
Data Wrangling: Gathering the Data You Need in a Form You Can Use
“Data! Data! Data!’ I can’t make bricks without clay.” – Sherlock Holmes
Before data science/machine learning/data mining/predictive analytics can be done, you need to have the data you are going to use. This may see obvious, but in many cases there is more to this step than may first be assumed, and the whole process is what I will call “data wrangling”, although has other names like “data munging”.
Data Surfing: The Oft Forgotten First Stage of Discovery
“You got to drift in the breeze before you set your sails. It’s an occupation where the wind prevails. Before you set your sails drift in the breeze.” – Paul Simon
Many texts about data science (including machine learning, data mining, and predictive analytics) don’t include much about the very first step of the process, which is the step where you come up with what your goal is for your other steps. In traditional science, this might be called the step of making your hypothesis.
The Four Major Activities of Data Science / Machine Learning
Recently there was a post on LinkedIn by Erle Hall, lead for the Information and Communication Technologies (ICT) for the California Department of Education (CDE) with a diagram about machine learning. That diagram had 6 steps: Select Data, Model Data, Validate Model, Test Model, Use the Model, and Tune Model. Those 6 steps mostly encapsulate what traditionally has been called the “data mining” phase. But there are 3 other important phases, which I will call “data surfing”, “data wrangling” and “data artistry”. (These names were chosen to be easier to understand and more interesting for students, but also go by different names) I also personally prefer to use the term “algorithm” instead of “model”, because while traditionally in data science, statistical models were used, there are now often times methods like neural networks and other such algorithms that are less like a traditional statistical model. In the next few posts, I’ll dive into each of these 4 steps, and give a basic explanation of what each step does, and why the step is important.
More thoughts on Drones / Flying Cars
Yesterday I posted about an NPR article about flying cars, and my opinion that the best way to make these a reality is to have them become laser powered. It is interesting that this week’s Economist also has an article about flying cars. If you thought this idea was far fetched, NASA has done some experiments of a proof of concept. But getting power to a drone/flying car alone is not enough, because there is still a need to have enough energy stored in the drone/flying car to stay aloft for s sufficient period of time if the incoming power stops working.
So, we also need a breakthrough in power storage, where more energy can be stored with less weight in a given space. Battery technology is not the long term answer. They weigh too much, charge too slowly, and have too short of an effective lifespan. This is why nanotube supercapacitors are what will be needed to have ubiquitous flying transportation become a reality.
Thought: Laser Powered Drones / Flying Cars
I have a tendency to be interested in a lot of different things, and try to think of solutions to problems. With a recent article I read about flying cars, it is clear that the biggest challenge is storing energy. But this could be solved in many places by having ground stations that used lasers to send energy to drones or even flying cars. In the countryside these could be attached to existing cell phone towers. They could also employ a safety system, where the main power beam is surrounded by smaller low power beams, and if those lose contact with a sensor in the drone, they will know something isn’t right, and shut down the main power beam.
If we did this, electric flying cars could become a reality fairly quickly….
The Early Archaeologist Hypothesis
I just read the NPR article: New Evidence Suggests Humans Arrived In The Americas Far Earlier Than Thought. And in the article it suggests that because cut bones were found in what is now Southern California, of a mastodon that is 130,000 years old, along with sharp rocks, that humans were on the American continent that long ago, instead of only 15,000 to 20,000 years ago. And while I think this hypothesis could be true, I want to advance another potential hypothesis: the early archaeologist / paleontologist hypothesis…
Thoughts from the California Information Communication Technologies Industry Advisory Committee
I flew down to San Diego last night to participate in the Statewide Information Communication Technologies (ICT) Industry Advisory Committee. It helped me to remember how important ICT education is. We had a great group of folks at the meeting, with a lot of passion and experience in supporting the students of California to becoming our next generation of “computer nerds”.
But it also brought back to me, about how our education system isn’t keeping up and changing for the needs of our next generation. Technology is our future, and of any industry sector (other than potentially energy), it is the use or abuse of technology will make the biggest difference to the future of human kind. And educational content standards, and the related curriculum, can either be what will give our students the knowledge that will be needed when they graduate; or force irrelevant content on them, leading to more disillusion with our education system; and at the same time lead to more unemployment.
The Secret PowerSchool Technical Manual: Unintended Consequences of Plugins
One of the reasons our school chose to go with PowerSchool, is that it has a higher degree of customization than many other SIS products. And when we first started with PowerSchool, we had a great consultant come out and help train our techs on how do much of this customization, and at the same time, he helped us do some of the initial customizations we needed. And in the end, to help us implement these customizations, he wrapped them up in to a plugin, and we were able to easily install them. And we thought that it would be easy for us to continue to customize things….
