Updated README.md

README.md

@@ -48,7 +48,7 @@
 
     ```
 
-- The saved model exceeds the size limit for GitHub uploads, so you'll need to download it from [Google Drive]() and place it inside the 'MLModelDev/fun1' folder as follows:
+- The saved model exceeds the size limit for GitHub uploads, so you'll need to download it from [Google Drive] and place it inside the 'MLModelDev/fun1' folder as follows:
 
 
 ---------------------
@@ -60,7 +60,7 @@
 
   - `self_improvement.py`: This service file include the total process of function 01.
     - input :Player database
-    - Attached models : rf_model.pkl ([Link](https://drive.google.com/drive/folders/1ENOy5CNJOgi1d9vrjqf7RRoieljmm7FJ?usp=drive_link))
+    
 
     - Process :firstly get the player dataset and caluculate the real time improvement ,compaired the previouse improvement score and get the future time(One week or two week) improvment prediction
     - Output : ID,Real_Time_predictions,Future_weeks_Predictions
@@ -70,7 +70,7 @@
 ### 5. Fast API & app file 
 - Within this app.py module include one Fast API end points for function 1 :
   - 1. Request body : Connect the real time played database and use the player_name to compil this function(player_name :rQIRSQe3ZYTRDGfvRb8dvzaCKkA2)
-       - Special Note:We need to create that database as mentioned in below link player_game_dataset.csv ([Link]( https://drive.google.com/drive/folders/1mRzLkdMJLO-5pc4vBxvdmv1B2WD5i2Lg?usp=drive_link))
+       - Special Note:We need to create that database as mentioned in below link player_game_dataset.csv 
       ```python
         @app.post("/function01/self_improvement")
         async def function1_self_improvementplayer_name:str):