Update README.md

Campus Placement Analysis & Prediction/README.md

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 # **Campus Placement Analysis & Prediction**
 
+Campus placement or campus recruiting is a program conducted within universities or other educational institutions to provide jobs to students nearing completion of their studies. In this type of program, the educational institutions partner with corporations who wish to recruit from the student population.
+
 **GOAL**
+
 To analyze various factors and predict salary offered to candidates during campus placements using machine learning algorithm.
 
 **DATASET**
 
 Dataset can be downloaded from [here](https://www.kaggle.com/benroshan/factors-affecting-campus-placement).
 
-**WHAT I HAD DONE**
+**WHAT I HAVE DONE**
 - Step 1: Data Preprocessing & Exploration
 - Step 2: Data Visualization
 - Step 3: Data Training & Model Creation
 - Step 4: Performance Evaluation
 
-
 **MODEL USED**
 -  Decision Tree Regressor
 
@@ -24,20 +26,34 @@ Dataset can be downloaded from [here](https://www.kaggle.com/benroshan/factors-a
 - seaborn
 - sklearn (For data traning, importing models and performance check)
 
+**Insights drawn through data visualization & analysis:**
+*   64.65% candidate are males and rest 35.35 % are females.
+*   Lowest SSC percentage among all candidates is 40.89% and highest is 89.4%.
+*   53.95 % of candidates gave their SSC exams under Central Board and rest 46.05% were from other board.
+*  Lowest HSC percentage among all candidates is 37.0% and highest is 97.7%.
+*  Only 39.07 % of candidates gave their HSC exams under Central Board and rest 60.93% were from other board.
+*  Among all the candidates 52.56% candidates are from commmerce stream, 42.33% candidates are from Science stream and rest 5.12% candidates are from Arts Stream.
+*  Lowest Degree percentage among all candidates is 50.0% and highest is 91.0%.
+*  Degree title of 67.44% candidates is Commerce & Management, for 27.44% candidates is Science & Technology and rest 5.12% have other degree title.
+*  65.58 % candidates have no work experience and rest 34.42% have valid work experience.
+*  Lowest Employability test percentage ( conducted by college) percentage among all candidates is 50.0% and highest is 98.0%.
+*  Among all the candidates 55.81% candidates have Marketing & Finance Post Graduation(MBA)- Specialization and rest 44.19 % have Marketing & HR Post Graduation(MBA)- Specialization.
+* Among all the candidates 68.84% candidates have been successfully placed and rest 31.16 % have not been placed.
+
 
-**Accuracy of different models used**
+
+**Accuracy of the model**
  - By using Decision Tree Regressor model 
  ```python
     Accuracy achieved :  1.00
  ``` 
 
-
-
 **CONCLUSION**
 
-Performance of Decision tree regressor is highyly efficient.
+*  Accuracy of the decision tree regressor model for this project is 1.00 which is an excellent accuracy.
 
+*  Decision tree regressor is a highly efficient model and widely used for regression tasks,various prediction projects etc.
 
 **Author** 
 
-[Ayushi Shrivastava](https://github.com/ayushi424)
+[Ayushi Shrivastava](https://github.com/ayushi424)