From 169ad3d2679906bc1e7b22eff03198f722e5872e Mon Sep 17 00:00:00 2001 From: BenFradet Date: Mon, 20 Apr 2015 13:46:55 -0700 Subject: [PATCH] [doc][streaming] Fixed broken link in mllib section The commit message is pretty self-explanatory. Author: BenFradet Closes #5600 from BenFradet/master and squashes the following commits: 108492d [BenFradet] [doc][streaming] Fixed broken link in mllib section --- docs/streaming-programming-guide.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md index 262512a639046..2f2fea53168a3 100644 --- a/docs/streaming-programming-guide.md +++ b/docs/streaming-programming-guide.md @@ -1588,7 +1588,7 @@ See the [DataFrames and SQL](sql-programming-guide.html) guide to learn more abo *** ## MLlib Operations -You can also easily use machine learning algorithms provided by [MLlib](mllib-guide.html). First of all, there are streaming machine learning algorithms (e.g. (Streaming Linear Regression](mllib-linear-methods.html#streaming-linear-regression), [Streaming KMeans](mllib-clustering.html#streaming-k-means), etc.) which can simultaneously learn from the streaming data as well as apply the model on the streaming data. Beyond these, for a much larger class of machine learning algorithms, you can learn a learning model offline (i.e. using historical data) and then apply the model online on streaming data. See the [MLlib](mllib-guide.html) guide for more details. +You can also easily use machine learning algorithms provided by [MLlib](mllib-guide.html). First of all, there are streaming machine learning algorithms (e.g. [Streaming Linear Regression](mllib-linear-methods.html#streaming-linear-regression), [Streaming KMeans](mllib-clustering.html#streaming-k-means), etc.) which can simultaneously learn from the streaming data as well as apply the model on the streaming data. Beyond these, for a much larger class of machine learning algorithms, you can learn a learning model offline (i.e. using historical data) and then apply the model online on streaming data. See the [MLlib](mllib-guide.html) guide for more details. ***