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Simplifying robust end-to-end machine learning on Apache Spark.

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We are using SparkContext throughout loaders and example pipelines. It makes sense to move these to using SparkSession given that we're relying on Spark 2.0.

May be unnecessary for Release 0.1

nodes
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The Least Squares Estimator should have the option to use a local least squares solver. A cost model needs to be built for it, and it needs to be added...

In addition to the gather operator which concatenates horizontally, it would be nice to have a union operator which concatenates veritcally. This came up in a discussion with @shivaram today...

enhancement
pipelines

Currently transformers are maps from `A => B`, but if I have some complex type like `(Int, Image)` I can't pass it into an `Image => DenseVector[Double]` Transformer and expect...

enhancement
pipelines

We often perform a sweep over lambdas to figure out the right regularization -- it matters a lot. @shivaram mentioned that it's possible for the weighted solver to potentially solve...

We don't necessarily iterate over images in a couple of common cases in a fast way, e.g. ``` scala while (x < numRows) { while (y < numCols) { while(c...

images