Fixed typos, updated Deep Learning PDF

dejurin · Dec 10, 2014 · 28b7ced · 28b7ced
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diff --git a/docs/deeplearning/DeepLearningBookletV1.pdf b/docs/deeplearning/DeepLearningBookletV1.pdf
diff --git a/docs/gbm/gbmRVignette.tex b/docs/gbm/gbmRVignette.tex
@@ -345,7 +345,7 @@ \subsection{Performing a trial run}
 
 \subsubsection{Extracting and handling the results}  
 
-Now, extract the parameters of the model, examine the scoring process, and make predictions on new data.
+Now, extract the parameters of the model, examine the scoring process, and make predictions on the new data.
 
 \begin{spverbatim}
 #View the specified parameters of your GBM model
@@ -359,7 +359,7 @@ \subsubsection{Extracting and handling the results}
 The second command ({\texttt{air.model}}) returns the trained model's training and validation errors. 
 \\
 \\
-After generating a satisfactory model, use the \texttt{h2o.predict()} command to compute and store predictions on new data, which can then be used for further tasks in the interactive modeling process.
+After generating a satisfactory model, use the \texttt{h2o.predict()} command to compute and store predictions on the new data, which can then be used for further tasks in the interactive modeling process.
 \begin{spverbatim}
 #Perform classification on the held out data
 prediction = h2o.predict(air.model, newdata=air_test.hex)
@@ -383,7 +383,7 @@ \subsubsection{Variable importances}
 
 \subsubsection{Java model}  
 
-To access Java (POJO) code to use to build the current model in Java, click \textsc{Java model} button in the top right of a model summary page. If the model is small enough, the code for the model displays within the GUI; larger models can be inspected after downloading the model.
+To access Java (POJO) code to use to build the current model in Java, click the \textsc{Java model} button in the top right of a model summary page. If the model is small enough, the code for the model displays within the GUI; larger models can be inspected after downloading the model.
 \\
 \\
 To download the model: 

diff --git a/docs/r/R_Vignette.tex b/docs/r/R_Vignette.tex
@@ -110,7 +110,7 @@ \subsection{Installing H2O in R}
 \subsection{Making a build from the Source Code}
 If you are a developer who wants to make changes to the R package before building and installing it, pull the source code from Git (\url{https://github.com/h2oai/h2o}) and follow the instructions in From Source Code (Github) at \url{http://docs.h2o.ai/developuser/quickstart\_git.html}.
 
-After making the build, navigate to the Rcran folder with the R package in the buildâ€™s directory, then run and install.
+After making the build, navigate to the Rcran folder with the R package in the build directory, then run and install.
 \begin{spverbatim}
 $ make clean
 $ make build
@@ -162,7 +162,7 @@ \subsection{Launching from R}
 
 If you are operating on a single node, initialize H2O using: \begin{spverbatim} h2o_server = h2o.init()\end{spverbatim}\\
 
-To connect with an existing H2O cluster node other than the default localhost:54321, specify the IP address and port number in the parentheses. For example:â€¨\begin{spverbatim}h2o_cluster = h2o.init(ip = "192.555.1.123", port = 12345)\end{spverbatim}
+To connect with an existing H2O cluster node other than the default localhost:54321, specify the IP address and port number in the parentheses. For example:\begin{spverbatim}h2o_cluster = h2o.init(ip = "192.555.1.123", port = 12345)\end{spverbatim}
 
 
 \subsection{Launching from the Command Line}