Update README.md

Author: ayushi424

Diff for: Machine Learning/Algorithms/Decision Tree Regressor/README.md

@@ -16,6 +16,7 @@ The main prupose is to give a clear understanding on what basically Decision Tre
 
 **DATASET**
 
+For the dataset being used in this project [click here](https://www.kaggle.com/benroshan/factors-affecting-campus-placement)
 
 
 
@@ -45,7 +46,21 @@ Here, in this project we will analyze various features that affect campus placem
 ![](https://github.com/ayushi424/DS-ScriptsNook/blob/main/Machine%20Learning/Algorithms/Decision%20Tree%20Regressor/Images/dtr4.jpg)
 ![](https://github.com/ayushi424/DS-ScriptsNook/blob/main/Machine%20Learning/Algorithms/Decision%20Tree%20Regressor/Images/dtr5.jpg)
 
-- Insights drawn through data visualization:
+ 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.
+
+
 
 
 3. Data training using train-test-split method from sklearn to split the data into training and testing data and then  Model creation using decision tree regressor algorithm, where we import the model, then initialize it and fit training data into it and lastly perform predictions on the test data.
@@ -64,7 +79,7 @@ Here, in this project we will analyze various features that affect campus placem
 
 **USAGE**
 - It is basically used for REGRESSION TASKS.
-- 
+- Various sectors as engineering, healthcare, education etc.
 
 **USE CASES**
 - Regression tasks.
@@ -106,9 +121,12 @@ Here, in this project we will analyze various features that affect campus placem
 *  It Can help in improving business plan by providing fruitful insights and prediction analysis.
 
 
-**REFERENCES**
+**Some beginner friendly REFERENCES**
 
-- 
+- https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeRegressor.html
+- https://scikit-learn.org/stable/auto_examples/tree/plot_tree_regression.html
+- https://www.geeksforgeeks.org/python-decision-tree-regression-using-sklearn/
+- https://towardsdatascience.com/machine-learning-basics-decision-tree-regression-1d73ea003fda
 
 
 **Author**