This is the third post in the Neural Net series.

Big Data analytics is a computer term used to describe the process of examining large data sets containing a variety of data types — to uncover hidden patterns, unknown correlations, market trends, customer preferences and other business information. The process involves looking at information through various “filters” or parameters.

Let’s consider the example of a data filter and suppose you are looking at your bank account online.  You can choose to look at your monthly statement, or all of your deposits, or search by a check number, a specific date, or a name. By applying the filter you are able to find the information you need quickly without searching all of the data. You are then able to use the data for analysis such as as “How much money am I spending every month on ______?”  etc.  This information is readily usable because of the filter.

Another example is a concept filter such as the Topics on the side of this blog. You can search this blog by various topics in an alphabetical list on the right side of this page. If you want to read more about pattern recognition specifically, you can double click on “pattern recognition”, and only the posts tagged with that term will show up in the search. Then you can read all of those posts dating from 2008 to this post. If you click on “The Neural Net”, you will see the links to all of the posts in this series.  This kind of filter allows you to research the same topic in various posts rather than reading chronologically which is the normal organization of this blog and others.

In learning, we can apply this concept of filter to optimize Pattern recognition. Examples of patterns could be scale and key patterns, chords, trills, rhythmic patterns, etc. By using previously learned material to review specific patterns and then applying the reviewed patterns to the new material , the students can learn how to learn by connecting their previous pieces with new concepts.  So, for example if the student is learning a piece in the key of G major, it is very useful to review Allegro from Book 1.  The right hand utilizes the G major scale pattern, and the left hand utilizes the primary chords.  The tactile feeling and sound of playing in G major,  the mental labels, and the visual symbols can all be reviewed in this piece. The student probably originally learned Allegro by ear, so it is very interesting to them to go back and “read” Allegro, and apply the new reading skills to the review piece. So, by reviewing this piece the student has access to the patterns they have previously learned and can then apply them to the new piece. There are several pieces in Book 2 in the key of G, as well as in later books.  Also, they can integrate and reinforce their reading skills with their book 1 pieces.  Additionally, by working on the scale and chords for technique in the key of G, and also having a new reading piece in the key of G the learning can be reinforced in all parts of the assignment.

The filters can be various concepts including keys, meter, rhythmic patterns (the minuets in Book 2 for example) style, harmonic patterns, trills, etc. By using selected review pieces that the student can apply specific skills to new pieces, and reinforce understanding, the learning can be built upon itself.  This way the review pieces can be rotated and reviewed when specific skills are needed.

Dr. Kataoka, founder of  Piano Basics said:

“If you can play Book 1, you can play anything.”

What I think she is referring to is that all of the basic patterns of playing piano are presented in Suzuki Piano Book 1.  Since the learning is built upon itself, the same concept of filter can be applied throughout the learning process so that the specific skills built in earlier pieces can be transferred and applied and developed in the more advanced pieces as the student progresses.

By learning the basic skills and patterns in each piece the student develops a foundation of learning, a framework upon which they can build ability.