Merge branch 'instate-docs' of https://github.com/EssamWisam/MLJFlux.jl…

… into instate-docs

docs/src/index.md

@@ -1,6 +1,6 @@
 # MLJFlux.jl
 
-A Julia package integrating deep learning Flux models with MLJ.
+A Julia package integrating deep learning Flux models with [MLJ](https://juliaai.github.io/MLJ.jl/dev/).
 
 ## Objectives
 
@@ -11,7 +11,7 @@ A Julia package integrating deep learning Flux models with MLJ.
 - Make it easier to apply machine learning techniques provided by MLJ, including: out-of-sample performance evaluation, hyper-parameter optimization, iteration control, and more, to deep learning models
 
 !!! note "MLJFlux Coverage"
-    MLJFlux support is focused on fundamental and widely used deep learning models; sophisticated architectures or techniques such as online learning, reinforcement learning, and adversarial networks are currently beyond its scope. 
+    MLJFlux support is focused on fundamental and widely used deep learning models.  Sophisticated architectures or techniques such as online learning, reinforcement learning, and adversarial networks are currently beyond its scope. 
 
 Also note that MLJFlux is limited to training models only when all training data fits into memory, though it still supports automatic batching of data.
 
@@ -25,7 +25,6 @@ Pkg.add(["MLJ", "MLJFlux", "Flux"])
 You only need `Flux` if you need to build a custom architecture or experiment with different optimizers, loss functions and activations.
 
 ## Quick Start
-First load and instantiate mode:
 ```@example
 using MLJ, Flux, MLJFlux
 import RDatasets