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This is the fifty second part of the ILP series. For your convenience you can find other parts in the table of contents in Part 1 – Boolean algebra In part 2 we saw how to calculate unsigned magnitude decomposition for non-negative integer variables. Today we are going to do the same for real variables. … Continue reading ILP Part 52 — Unsigned magnitude decomposition for real variables
This is the fifty first part of the ILP series. For your convenience you can find other parts in the table of contents in Part 1 – Boolean algebra This is the fifth part of the ML series. For your convenience you can find other parts in the table of contents in Part 1 – … Continue reading Machine Learning Part 5, ILP Part 51 — Linear regression
This is the fourth part of the ML series. For your convenience you can find other parts in the table of contents in Part 1 – Linear regression in MXNet This time we are going to implement linear regression as a function. This gives us a little more flexibility in terms of debugging the code … Continue reading Machine Learning Part 4 — Linear regression in T-SQL
This is the third part of the ML series. For your convenience you can find other parts in the table of contents in Part 1 – Linear regression in MXNet Last time we saw how to calculate linear regression for the Iris dataset. However, we had to hardcode all the featuers. Today we are going … Continue reading Machine Learning Part 3 — Linear regression in SQL revisited