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This is the eighth 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 forward propagation in neural net. Today we are going to extend the process to backpropagate the errors. Let’s begin. We need … Continue reading Machine Learning Part 8 — Backpropagation in neural net in SQL
This is the seventh 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 Today we are going to create a neural net and calculate forward propagation using PostgreSQL. Let’s go. We start with definition of the network: we … Continue reading Machine Learning Part 7 — Forward propagation in neural net in SQL
This is the sixth 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 Today we are going to implement a matrix multiplication in Redshift. Let’s go. First, let’s see what we want to calculate: Nothing fancy. … Continue reading Machine Learning Part 6 — Matrix multiplication in SQL
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