✨ Add 7 workflow examples for MLJFlux

.gitignore

@@ -6,4 +6,5 @@
 .DS_Store
 sandbox/
 docs/build
-/examples/mnist/mnist_machine*
+/examples/mnist/mnist_machine*
+Manifest.toml

docs/make.jl

@@ -34,15 +34,19 @@ makedocs(
                 "Image Classification"=>"interface/Image Classification.md",
             ],
             "Workflow Examples" => Any[
-                "Incremental Training"=>"workflow examples/Incremental Training.md",
-                #"Validation and Hyperparameter Tuning"=>"workflow examples/Hyperparameter Tuning.md",
-                #"Early Stopping"=>"workflow examples/Early Stopping.md",
-                #"Model Composition"=>"workflow examples/Composition.md",
+                "Incremental Training"=>"workflow examples/Incremental Training/incremental.md",
+                "Hyperparameter Tuning"=>"workflow examples/Hyperparameter Tuning/tuning.md",
+                "Neural Architecture Search"=>"workflow examples/Basic Neural Architecture Search/tuning.md",
+                "Model Composition"=>"workflow examples/Composition/composition.md",
+                "Model Comparison"=>"workflow examples/Comparison/comparison.md",
+                "Early Stopping"=>"workflow examples/Early Stopping/iteration.md",
+                "Live Training"=>"workflow examples/Live Training/live-training.md",
+            ],
+            "Tutorials"=>Any[
+                # "MNIST Digits Classification"=>"full tutorials/MNIST.md",
+                # "Boston House Prices Prediction"=>"full tutorials/Boston.md",
+                "Spam Detection with RNNs"=>"full tutorials/Spam Detection with RNNs/SMS.md"
             ],
-            # "Tutorials"=>Any[
-            #     "MNIST Digits Classification"=>"full tutorials/MNIST.md",
-            #     "Boston House Prices Prediction"=>"full tutorials/Boston.md",
-            # ],
             "Contributing" => "contributing.md"],
         doctest = false,
 )

docs/src/full tutorials/Spam Detection with RNNs/Project.toml

@@ -0,0 +1,11 @@
+[deps]
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+Languages = "8ef0a80b-9436-5d2c-a485-80b904378c43"
+Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
+MLJFlux = "094fc8d1-fd35-5302-93ea-dabda2abf845"
+MLJText = "5e27fcf9-6bac-46ba-8580-b5712f3d6387"
+ScientificTypes = "321657f4-b219-11e9-178b-2701a2544e81"
+TextAnalysis = "a2db99b7-8b79-58f8-94bf-bbc811eef33d"
+WordTokenizers = "796a5d58-b03d-544a-977e-18100b691f6e"