✏️ Attempt for a better link for Quick Start

FluxML · Jun 10, 2024 · e182bd0 · e182bd0
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Showing 18 changed files with 21 additions and 21 deletions.
diff --git a/docs/src/workflow examples/Basic Neural Architecture Search/tuning.ipynb b/docs/src/workflow examples/Basic Neural Architecture Search/tuning.ipynb
@@ -94,7 +94,7 @@
   {
    "cell_type": "markdown",
    "source": [
-    "Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md)."
+    "Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md#Quick-Start)."
    ],
    "metadata": {}
   },

diff --git a/docs/src/workflow examples/Basic Neural Architecture Search/tuning.jl b/docs/src/workflow examples/Basic Neural Architecture Search/tuning.jl
@@ -28,7 +28,7 @@ first(X, 5)
 
 # ### Instantiating the model
 
-# Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md).
+# Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md#Quick-Start).
 NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg = "MLJFlux"
 clf = NeuralNetworkClassifier(
 	builder = MLJFlux.MLP(; hidden = (1, 1, 1), σ = Flux.relu),

diff --git a/docs/src/workflow examples/Basic Neural Architecture Search/tuning.md b/docs/src/workflow examples/Basic Neural Architecture Search/tuning.md
@@ -30,7 +30,7 @@ first(X, 5)
 
 ### Instantiating the model
 
-Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md).
+Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md#Quick-Start).
 
 ````@example tuning
 NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg = "MLJFlux"

diff --git a/docs/src/workflow examples/Comparison/comparison.ipynb b/docs/src/workflow examples/Comparison/comparison.ipynb
@@ -61,7 +61,7 @@
    "cell_type": "markdown",
    "source": [
     "### Instantiating the models\n",
-    "Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md)."
+    "Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md#Quick-Start)."
    ],
    "metadata": {}
   },

diff --git a/docs/src/workflow examples/Comparison/comparison.jl b/docs/src/workflow examples/Comparison/comparison.jl
@@ -22,7 +22,7 @@ y, X = unpack(iris, ==(:Species), colname -> true, rng=123);
 
 
 # ### Instantiating the models
-# Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md).
+# Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md#Quick-Start).
 
 NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg=MLJFlux
 

diff --git a/docs/src/workflow examples/Comparison/comparison.md b/docs/src/workflow examples/Comparison/comparison.md
@@ -25,7 +25,7 @@ y, X = unpack(iris, ==(:Species), colname -> true, rng=123);
 ````
 
 ### Instantiating the models
-Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md).
+Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md#Quick-Start).
 
 ````julia
 NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg=MLJFlux

diff --git a/docs/src/workflow examples/Early Stopping/iteration.ipynb b/docs/src/workflow examples/Early Stopping/iteration.ipynb
@@ -62,7 +62,7 @@
    "cell_type": "markdown",
    "source": [
     "### Instantiating the model\n",
-    "Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md)."
+    "Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md#Quick-Start)."
    ],
    "metadata": {}
   },

diff --git a/docs/src/workflow examples/Early Stopping/iteration.jl b/docs/src/workflow examples/Early Stopping/iteration.jl
@@ -23,7 +23,7 @@ X = Float32.(X);      # To be compatible with type of network network parameters
 
 
 # ### Instantiating the model
-# Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md).
+# Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md#Quick-Start).
 
 NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg=MLJFlux
 

diff --git a/docs/src/workflow examples/Early Stopping/iteration.md b/docs/src/workflow examples/Early Stopping/iteration.md
@@ -27,7 +27,7 @@ nothing #hide
 ````
 
 ### Instantiating the model
-Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md).
+Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md#Quick-Start).
 
 ````@example iteration
 NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg=MLJFlux

diff --git a/docs/src/workflow examples/Hyperparameter Tuning/tuning.ipynb b/docs/src/workflow examples/Hyperparameter Tuning/tuning.ipynb
@@ -62,7 +62,7 @@
    "cell_type": "markdown",
    "source": [
     "### Instantiating the model\n",
-    "Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md)."
+    "Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md#Quick-Start)."
    ],
    "metadata": {}
   },

diff --git a/docs/src/workflow examples/Hyperparameter Tuning/tuning.jl b/docs/src/workflow examples/Hyperparameter Tuning/tuning.jl
@@ -24,7 +24,7 @@ X = Float32.(X);      # To be compatible with type of network network parameters
 
 
 # ### Instantiating the model
-# Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md).
+# Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md#Quick-Start).
 
 NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg=MLJFlux
 clf = NeuralNetworkClassifier(

diff --git a/docs/src/workflow examples/Hyperparameter Tuning/tuning.md b/docs/src/workflow examples/Hyperparameter Tuning/tuning.md
@@ -27,7 +27,7 @@ nothing #hide
 ````
 
 ### Instantiating the model
-Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md).
+Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md#Quick-Start).
 
 ````@example Tuning
 NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg=MLJFlux

diff --git a/docs/src/workflow examples/Incremental Training/incremental.ipynb b/docs/src/workflow examples/Incremental Training/incremental.ipynb
@@ -59,7 +59,7 @@
    "cell_type": "markdown",
    "source": [
     "### Instantiating the model\n",
-    "Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md)."
+    "Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md#quick-start)."
    ],
    "metadata": {}
   },
@@ -76,7 +76,7 @@
     {
      "output_type": "execute_result",
      "data": {
-      "text/plain": "NeuralNetworkClassifier(\n  builder = MLP(\n        hidden = (5, 4), \n        σ = NNlib.relu), \n  finaliser = NNlib.softmax, \n  optimiser = Adam(0.01, (0.9, 0.999), 1.0e-8, IdDict{Any, Any}()), \n  loss = Flux.Losses.crossentropy, \n  epochs = 10, \n  batch_size = 8, \n  lambda = 0.0, \n  alpha = 0.0, \n  rng = 42, \n  optimiser_changes_trigger_retraining = false, \n  acceleration = CPU1{Nothing}(nothing))"
+      "text/plain": "NeuralNetworkClassifier(\n  builder = MLP(\n        hidden = (5, 4), \n        σ = NNlib.relu), \n  finaliser = NNlib.softmax, \n  optimiser = Flux.Optimise.Adam(0.01, (0.9, 0.999), 1.0e-8, IdDict{Any, Any}()), \n  loss = Flux.Losses.crossentropy, \n  epochs = 10, \n  batch_size = 8, \n  lambda = 0.0, \n  alpha = 0.0, \n  rng = 42, \n  optimiser_changes_trigger_retraining = false, \n  acceleration = ComputationalResources.CPU1{Nothing}(nothing))"
      },
      "metadata": {},
      "execution_count": 3
@@ -111,13 +111,13 @@
      "output_type": "stream",
      "text": [
       "[ Info: Training machine(NeuralNetworkClassifier(builder = MLP(hidden = (5, 4), …), …), …).\n",
-      "\rOptimising neural net:  18%[====>                    ]  ETA: 0:00:00\u001b[K\rOptimising neural net:  27%[======>                  ]  ETA: 0:00:00\u001b[K\rOptimising neural net:  36%[=========>               ]  ETA: 0:00:00\u001b[K\rOptimising neural net:  45%[===========>             ]  ETA: 0:00:00\u001b[K\rOptimising neural net:  55%[=============>           ]  ETA: 0:00:00\u001b[K\rOptimising neural net:  64%[===============>         ]  ETA: 0:00:00\u001b[K\rOptimising neural net:  73%[==================>      ]  ETA: 0:00:00\u001b[K\rOptimising neural net:  82%[====================>    ]  ETA: 0:00:00\u001b[K\rOptimising neural net:  91%[======================>  ]  ETA: 0:00:00\u001b[K\rOptimising neural net: 100%[=========================] Time: 0:00:00\u001b[K\n"
+      "\rOptimising neural net:  18%[====>                    ]  ETA: 0:00:21\u001b[K\rOptimising neural net: 100%[=========================] Time: 0:00:05\u001b[K\n"
      ]
     },
     {
      "output_type": "execute_result",
      "data": {
-      "text/plain": "trained Machine; caches model-specific representations of data\n  model: NeuralNetworkClassifier(builder = MLP(hidden = (5, 4), …), …)\n  args: \n    1:\tSource @609 ⏎ Table{AbstractVector{Continuous}}\n    2:\tSource @135 ⏎ AbstractVector{Multiclass{3}}\n"
+      "text/plain": "trained Machine; caches model-specific representations of data\n  model: NeuralNetworkClassifier(builder = MLP(hidden = (5, 4), …), …)\n  args: \n    1:\tSource @655 ⏎ ScientificTypesBase.Table{AbstractVector{ScientificTypesBase.Continuous}}\n    2:\tSource @902 ⏎ AbstractVector{ScientificTypesBase.Multiclass{3}}\n"
      },
      "metadata": {},
      "execution_count": 4

diff --git a/docs/src/workflow examples/Incremental Training/incremental.jl b/docs/src/workflow examples/Incremental Training/incremental.jl
@@ -25,7 +25,7 @@ X = Float32.(X)      # To be compatible with type of network network parameters
 
 
 # ### Instantiating the model
-# Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md).
+# Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md#Quick-Start).
 
 NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg=MLJFlux
 clf = NeuralNetworkClassifier(

diff --git a/docs/src/workflow examples/Incremental Training/incremental.md b/docs/src/workflow examples/Incremental Training/incremental.md
@@ -29,7 +29,7 @@ nothing #hide
 ````
 
 ### Instantiating the model
-Now let's construct our model. This follows a similar setup the one followed in the [Quick Start](../../index.md).
+Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md#quick-start).
 
 ````@example incremental
 NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg=MLJFlux

diff --git a/docs/src/workflow examples/Live Training/live-training.ipynb b/docs/src/workflow examples/Live Training/live-training.ipynb
@@ -55,7 +55,7 @@
    "cell_type": "markdown",
    "source": [
     "### Instantiating the model\n",
-    "Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md)."
+    "Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md#Quick-Start)."
    ],
    "metadata": {}
   },

diff --git a/docs/src/workflow examples/Live Training/live-training.jl b/docs/src/workflow examples/Live Training/live-training.jl
@@ -21,7 +21,7 @@ X = Float32.(X);      # To be compatible with type of network network parameters
 
 
 # ### Instantiating the model
-# Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md).
+# Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md#Quick-Start).
 
 NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg=MLJFlux
 

diff --git a/docs/src/workflow examples/Live Training/live-training.md b/docs/src/workflow examples/Live Training/live-training.md
@@ -25,7 +25,7 @@ nothing #hide
 ````
 
 ### Instantiating the model
-Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md).
+Now let's construct our model. This follows a similar setup to the one followed in the [Quick Start](../../index.md#Quick-Start).
 
 ````@example live-training
 NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg=MLJFlux