Update README.md

README.md

@@ -29,14 +29,14 @@ The model has not undergone clinical testing  and usage is at ueser's own risk.T
 
 #How to use
 Download the pre-trained model and use it to make inference.
-A space has been created for testing (here)[space.com]
+A space has been created for testing [here](space.com)
 
 #Training data
 The entire dataset consist of 3500 negative images and 700 positive TB images. </br>
 The data was splitted in 80% for training and 20% for validation.
 
 #Training procedure
-Transfer-learning was employed using InceptionV3 as the pre-trained model. Training was done for 20 epochs and the classes were weighted during training in order to neutralize the imbalanced class in the dataset. The training was done on Kaggle using the GPUs provided. More details of the experiments can be found (here)[https://www.kaggle.com/code/abrahamowodunni/tb-project]
+Transfer-learning was employed using InceptionV3 as the pre-trained model. Training was done for 20 epochs and the classes were weighted during training in order to neutralize the imbalanced class in the dataset. The training was done on Kaggle using the GPUs provided. More details of the experiments can be found [here](https://www.kaggle.com/code/abrahamowodunni/tb-project)
 
 #Evaluation results
 The result of the evaluation are as follows: - loss: 0.0923 - binary_accuracy: 0.9857 - precision: 0.9259 - recall: 0.9843