Update docs (#71)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

docs/sdk.md

@@ -1,11 +1,70 @@
-# Python SDK
+## Using YOLO models
+This is the simplest way of simply using yolo models in a python environment. It can be imported from the `ultralytics` module.
 
-We provide 2 pythonic interfaces for YOLO models:
+!!! example "Usage"
+    === "Training"
+        ```python
+        from ultralytics import YOLO
 
-<b> Model Interface </b> - To simply build, load, train or run inference on a model in a python application
+        model = YOLO()
+        model.new("n.yaml") # pass any model type
+        model.train(data="coco128.yaml", epochs=5)
+        ```
 
-<b> Trainer Interface </b> - To customize trainier elements depending on the task. Suitable for R&D ideas like architecutres.
+    === "Training pretrained"
+        ```python
+        from ultralytics import YOLO
 
-______________________________________________________________________
+        model = YOLO()
+        model.load("n.pt") # pass any model type
+        model(...) # inference
+        model.train(data="coco128.yaml", epochs=5)
+        ```
 
-### Model Interface
+    === "Resume Training"
+        ```python
+        from ultralytics import YOLO
+
+        model = YOLO()
+        model.resume(task="detect") # resume last detection training
+        model.resume(task="detect", model="last.pt") # resume from a given model
+        ```
+
+    More functionality coming soon
+
+To know more about using `YOLO` models, refer Model class refernce
+
+[Model reference](#){ .md-button .md-button--primary}
+
+---
+### Customizing Tasks with Trainers
+`YOLO` model class is a high-level wrapper on the Trainer classes. Each YOLO task has its own trainer that inherits from `BaseTrainer`. 
+You can easily cusotmize Trainers to support custom tasks or explore R&D ideas.
+
+!!! tip "Trainer Examples"
+    === "DetectionTrainer"
+        ```python
+        from ultralytics import yolo
+
+        trainer = yolo.DetectionTrainer(data=..., epochs=1) # override default configs
+        trainer.train()
+        ```
+
+    === "SegmentationTrainer"
+        ```python
+        from ultralytics import yolo
+
+        trainer = yolo.SegmentationTrainer(data=..., epochs=1) # override default configs
+        trainer.train()
+        ```
+    === "ClassificationTrainer"
+        ```python
+        from ultralytics import yolo
+
+        trainer = yolo.ClassificationTrainer(data=..., epochs=1) # override default configs
+        trainer.train()
+        ```
+
+Learn more about Customizing `Trainers`, `Validators` and `Predictors` to suit your project needs in the Customization Section. More details about the base engine classes is available in the reference section.
+
+[Customization tutorials](#){ .md-button .md-button--primary}