diff --git a/CMake/FindGo.cmake b/CMake/FindGo.cmake
index e4a0af57d4..dfccd8a9fe 100644
--- a/CMake/FindGo.cmake
+++ b/CMake/FindGo.cmake
@@ -19,10 +19,6 @@ if (GO_EXECUTABLE)
     endif()
 endif()
 
-if (NOT GO_EXECUTABLE)
-  unset(BUILD_GO_BINDINGS CACHE)
-endif()
-
 include(FindPackageHandleStandardArgs)
 find_package_handle_standard_args(
     Go
diff --git a/doc/guide/go_quickstart.hpp b/doc/guide/go_quickstart.hpp
index 64c130c4e3..9a67642857 100644
--- a/doc/guide/go_quickstart.hpp
+++ b/doc/guide/go_quickstart.hpp
@@ -15,7 +15,8 @@ and @ref julia_quickstart "Julia".
 
 @section go_quickstart_install Installing mlpack
 
-Installing the mlpack bindings for Go is somewhat ticker; you can download
+Installing the mlpack bindings for Go is somewhat time-consuming as the library
+must be built; you can run the following code:
 
 @code{.sh}
 go get -d mlpack.org/v1/mlpack
@@ -53,16 +54,10 @@ func main() {
 
   // Extract/Unzip the dataset.
   mlpack.UnZip("data.csv.gz", "data.csv")
-  f1, _ := os.Open("data.csv")
-  defer f1.Close()
-  data := mlpack.NewReader(f1)
-  dataset, _ := data.ReadAll()
+  dataset, _ := mlpack.Load("data.csv")
 
   mlpack.UnZip("labels.csv.gz", "labels.csv")
-  f2, _ := os.Open("labels.csv")
-  defer f2.Close()
-  labels_data := mlpack.NewReader(f2)
-  labels, _ := labels_data.ReadAll()
+  labels, _ := mlpack.Load("labels.csv")
 
   // Split the dataset using mlpack.
   params := mlpack.PreprocessSplitOptions()
@@ -154,11 +149,7 @@ func main() {
 
   // Extract dataset.
   mlpack.UnZip("ratings-only.csv.gz", "ratings-only.csv")
-  f1, _ := os.Open("ratings-only.csv")
-  defer f1.Close()
-  data := mlpack.NewReader(f1)
-  _, _ = data.ReadHeading()
-  ratings, _ := data.ReadAll()
+  ratings, _ := mlpack.Load("ratings-only.csv")
 
   mlpack.UnZip("movies.csv.gz", "movies.csv")
   table, _ := csv.NewTable(csv.FromFile("movies.csv"), csv.LoadHeaders())
@@ -168,8 +159,7 @@ func main() {
   params := mlpack.PreprocessSplitOptions()
   params.TestRatio = 0.1
   params.Verbose = true
-  ratings_test, _, ratings_train, _ :=
-      mlpack.PreprocessSplit(ratings, params)
+  ratings_test, _, ratings_train, _ := mlpack.PreprocessSplit(ratings, params)
 
   // Train the model.  Change the rank to increase/decrease the complexity of the
   // model.
diff --git a/src/mlpack/bindings/go/CMakeLists.txt b/src/mlpack/bindings/go/CMakeLists.txt
index d626c2280c..72b5c76549 100644
--- a/src/mlpack/bindings/go/CMakeLists.txt
+++ b/src/mlpack/bindings/go/CMakeLists.txt
@@ -1,4 +1,9 @@
 if (BUILD_GO_BINDINGS)
+
+  if (NOT GO_EXECUTABLE)
+    unset(BUILD_GO_BINDINGS CACHE)
+  endif()
+
   ## We need to check here if Golang is even available.  Although actually
   ## technically, I'm not sure if we even need to know!  For the tests though we
   ## do.  So it's probably a good idea to check.
@@ -61,6 +66,7 @@ if (BUILD_GO_SHLIB)
     mlpack/arma_util.go
     mlpack/cli_util.go
     mlpack/doc.go
+    mlpack/numcsv.go
   )
 
   # These are all the files we need to compile Go bindings for mlpack that are
diff --git a/src/mlpack/bindings/go/mlpack/numcsv.go b/src/mlpack/bindings/go/mlpack/numcsv.go
new file mode 100644
index 0000000000..15f1b14d89
--- /dev/null
+++ b/src/mlpack/bindings/go/mlpack/numcsv.go
@@ -0,0 +1,135 @@
+package mlpack
+
+import (
+	"encoding/csv"
+	"io"
+	"os"
+	"strconv"
+	"net/http"
+	"compress/gzip"
+
+        "gonum.org/v1/gonum/mat"
+)
+
+// Load reads all of the numeric records from the CSV.
+func Load(filename string) (*mat.Dense, error) {
+  var elements int
+  var rows int
+  var numbers []float64
+
+  // Open the file
+  file, err := os.Open(filename)
+  if err != nil {
+    return nil, err
+  }
+  defer file.Close()
+
+  lines, err := csv.NewReader(file).ReadAll()
+  if err != nil {
+    return nil, err
+  }
+  
+  var str_err error
+  for _, args := range lines[0:] {
+    for _, arg := range args {
+      n, err := strconv.ParseFloat(arg, 64)
+      str_err = err 
+      if err == nil {
+        numbers = append(numbers, n)
+        elements = elements + 1
+      }
+    }
+    if str_err == nil {
+      rows = rows + 1
+    }
+  }
+  data := numbers[:elements]
+  columns := elements/rows
+  output := mat.NewDense(rows , columns, data)
+  return output, nil
+}
+
+// Save writes all of the records to the CSV.
+func Save(filename string, mat *mat.Dense) error {
+  // Create the file
+  file, err := os.Create(filename)
+  if err != nil {
+    return err
+  }
+  defer file.Close()
+
+  writer := csv.NewWriter(file)
+  defer writer.Flush()
+
+  if mat != nil {
+    rows, cols := mat.Dims()
+    for i := 0; i < rows; i++ {
+      var strings []string
+      for j := 0; j < cols; j++ {
+        s := strconv.FormatFloat(mat.At(i,j), 'e', 16, 64)
+        strings = append(strings, s)
+      }
+      err := writer.Write(strings)
+      if err != nil {
+        return err
+      }
+    }
+  }
+  return nil
+}
+
+// Unizp unzips the given input to the given the output file.
+func UnZip(input string, output string) error {
+    // Create the file
+    out, err := os.Create(output)
+    if err != nil {
+        return err
+    }
+    defer out.Close()
+
+    // Open the file
+    in, err := os.Open(input)
+    if err != nil {
+        return err
+    }
+    defer in.Close()
+    
+    // Unzip the data
+    resp, err := gzip.NewReader(in)
+    if err != nil {
+        return err
+    }
+    defer resp.Close()
+
+    // Write the body to file
+    _, err = io.Copy(out, resp)
+    if err != nil {
+        return err
+    }
+    return nil
+}
+
+// DownloadFile downloads the file from the given url and save it to the given filename.
+func DownloadFile (url string, filename string) error {
+    // Create the file
+    out, err := os.Create(filename)
+    if err != nil {
+        return err
+    }
+    defer out.Close()
+
+    // Get the data
+    resp, err := http.Get(url)
+    if err != nil {
+        return err
+    }
+    defer resp.Body.Close()
+
+    // Write the body to file
+    _, err = io.Copy(out, resp.Body)
+    if err != nil {
+        return err
+    }
+
+    return nil
+}