Updating ado net datasets with visual basic 2016 lib

02-Jul-2020 13:26 by 7 Comments

Updating ado net datasets with visual basic 2016 lib

You can read about the data and its properties here, but at a high level, there is a bunch of data about flower dimensions (pedal length/width & Sepal length/width) and a classification of 3 types of Iris species.The goal is to use the data to create a model to predict the species of Iris based on the dimensions as input.

Unfortunately, there are no native libraries to do this Marshaling between data types so I wrote a quick helper function to do a single-level of parsing for you: With this function in hand, calling Parse Setup and Parse is very straightforward once you know the parameters.

This brings us to the biggest issue with the API as it lives today in v3.

The challenge is that the Post data does not accept JSON, but all of the return data from API is JSON.

Even with libraries that implement the various algorithms, it simply required a ton of work to even get to the point where you could train a set of data.

Tuning that usually required graduate-level understanding of each algorithm and the math behind it.

It comes with a set of libraries for python, java, and R, it has a REST API (which we will leverage today), and it even has a GUI if you want to stay out of code entirely.

Personally, I find the web GUI great, but use it mostly for examining data I’ve loaded or to quickly do something when I don’t feel like looking up the API/lib call.If you’ve toyed in this space without getting serious, then you probably have a similar story.All of that changed for me when starting to play with the python library SKLearn (won’t be discussing today) and the cross-platform open environment for analytics/machine learning called H2o.URL $deeplearning_url = $url -f "Model Builders/deeplearning" $deeplearning_body = 'training_frame=train&response_column=class&model_id=neural' $ret = invoke-restmethod $deeplearning_url -Method Post -Body $deeplearning_body wait-H2o Job $key.URL In the above, we are saying to use the data set named “train” and that we will be using the data in the columns to predict the column named “class”.Full disclosure, there is still some art to tweaking the algorithms and data to get an optimal data model, H2o makes it much easier. I promise you’ll have a deep learning neural net training a data model in only a few minutes.

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