WebGL is really a fascinating topic to me. Being able to utilize the power of a local machine’s GPU via the web browser is a very novel concept.
If one was to ask back in 1996 would you be able to render Open GL code in a web browser via GPU, even the most tech savvy may have replied, “Open GL? GPU? what are those things, you speak about?”
Will take the ngrams, reading and writing from the SQLite database and train the model utilizing Katz-Backoff methodology on the likelihood of the next word.
See code below
Using a list, load RDS formatted files into standard data frame. Allows for grouping multiple files into one data frame for processing.
See code below
I wrote an interface class to help with working with the SQLite database.
Methods include, selectQuery, updateQuery, readTable, writeTable
see code below
Traverse the tree in natural order and test if each node is between the previous and the next node. Properly detect duplicate values. If a wrong sub-tree is encountered immediately stop the script and indicate the error.
See code below
Standard problem of trying to maximize the values of item with a constraint. How many items can you put in a knapsack given the value and the weight of the items.
Uses python3
goal: maximize the value of items selected from the get_optimal_value
while the items selected combined weight is less than the inputted capacity
Binary Search Problem
Function below handles a simple search for a needle in a haystack using the binary search algorithm.
The function is called recursively to check if a value is inside the array
See python code below.
“Making a square peg fit into a round hole”
There are many times when dealing with data that you need to transfigure one data set to allow for comparison purposes.
SQL has built in functions that easily allow us to transfigure data. There are some considerations when using the functions, most importantly understanding what will happen to the data set during the process.
Today I will talk about the CAST function.
Function to take a vector of length n and multiply the two largest values in the vector.
See the code below
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