✨ Further improve docs

Author: EssamWisam

src/mlj_embedder_interface.jl

@@ -119,7 +119,6 @@ Train the machine using `fit!(mach)`.
 ```julia
 using MLJ
 using CategoricalArrays
-import Pkg; Pkg.add("MLJLIBSVMInterface")       # For SVC
 
 # Setup some data
 N = 200
@@ -142,7 +141,6 @@ NeuralNetworkClassifier = @load NeuralNetworkClassifier pkg=MLJFlux
 SVC = @load SVC pkg=LIBSVM              
 
 
-
 emb = EntityEmbedder(NeuralNetworkClassifier(embedding_dims=Dict(:Column2 => 2, :Column3 => 2)))
 clf = SVC(cost = 1.0)
 
@@ -174,15 +172,15 @@ yhat = predict(mach, X)
 machy = machine(emb, X, y)
 fit!(machy)
 julia> Xnew = transform(machy, X)
-(Column1 = Float32[1.0, 2.0, 3.0, 4.0, 5.0, 1.0, … ],
- Column2_1 = Float32[1.285769, 0.08033762, -0.09961729, -0.2812789, 0.94185555, 1.285769,  … ],
- Column2_2 = Float32[-0.8712612, -0.34193662, -0.8327084, 1.6905315, 0.75170106, -0.8712612,  …],
- Column3_1 = Float32[-0.00044717162, 1.5679433, -0.48835647, -0.9364795, -0.9364795, -0.00044717162, …],
- Column3_2 = Float32[-1.086054, 1.1133554, -1.5444189, 0.2760421, 0.2760421, -1.086054,  … ],
+(Column1 = Float32[1.0, 2.0, 3.0, … ],
+ Column2_1 = Float32[1.2, 0.08, -0.09, -0.2, 0.94, 1.2,  … ],
+ Column2_2 = Float32[-0.87, -0.34, -0.8, 1.6, 0.75, -0.87,  …],
+ Column3_1 = Float32[-0.0, 1.56, -0.48, -0.9, -0.9, -0.0, …],
+ Column3_2 = Float32[-1.0, 1.1, -1.54, 0.2, 0.2, -1.0,  … ],
  Column4 = Float32[1.0, 2.0, 3.0, 4.0, 5.0, 1.0, … ],
- Column5 = Float32[0.27364022, 0.12229505, -0.60269946, 1.5815768, -0.6342952, -0.12323896, … ],
- Column6_1 = Float32[-0.99640805, -0.99640805, 0.8055623, 0.8055623, 0.34632754, -0.99640805, … ],
- Column6_2 = Float32[-1.0043539, -1.0043539, 0.19345926, 0.19345926, 1.7287723, -1.0043539, … ])
+ Column5 = Float32[0.27, 0.12, -0.60, 1.5, -0.6, -0.123, … ],
+ Column6_1 = Float32[-0.99, -0.99, 0.8, 0.8, 0.34, -0.99, … ],
+ Column6_2 = Float32[-1.00, -1.0, 0.19, 0.19, 1.7, -1.00, … ])
 ```
 
 See also