Update machine-learning/03-Training and AutoML.ipynb

Co-authored-by: Luis Quintanilla <46974588+luisquintanilla@users.noreply.github.com>

Author: LittleLittleCloud

machine-learning/03-Training and AutoML.ipynb

@@ -230,7 +230,7 @@
       "metadata": {},
       "source": [
         "## Train and evaluate model\n",
-        "The code below first trains `sdcaPipeline` and `lgbmPipeline` which are created above, then evaluate their performance on test dataset by calcuate `Root Mean Square Loss` between predicted and truth value. We can see that `SDCA` has better performance with a significant lower `Root Mean Square Loss` comparing with `LightGbm`, even it's a simple, linear model. This is because the training dataset is also linear, so `SDCA` can fit the dataset better than `LightGbm`."
+        "The code below first trains `sdcaPipeline` and `lgbmPipeline` which are created above, then evaluate their performance on test dataset by calculating `Root Mean Square Loss` between predicted and actual value. `SDCA` has better performance with a significantly lower `Root Mean Square Loss` compared to `LightGbm` even though it's a simpler linear model. This is because the training dataset is also linear, so `SDCA` can fit the dataset better than `LightGbm`."
       ]
     },
     {