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+### Entrepreneurial Capacity in Student
+   **GOAL**
+   ##### To Create a machine learning model with highest accuracy which will predict the Entrepreneurial Capacity in Student.
+   **DATASET**
+   ##### [LINK](https://www.kaggle.com/namanmanchanda/entrepreneurial-competency-in-university-students)
+   **DESCRIPTION**
+   ##### Entrepreneurs have been shaping the world in every way possible. The dataset comprises 16 features collected from university students in India. The target variable consists whether the student is likely to become an entrepreneur or not. Hence, we need to classify the dataset into whether the student is likely to become an enterpreneur or not.
+   **WHAT I HAD DONE**
+   ##### 1. Imported libraries required
+   ##### 2. Extracted data from kaggle
+   ##### 3. Prepared dataset 
+   ##### 4. Performed exploratory data analysis on updated data
+   ##### 5. Split data for training and testing purpose
+   ##### 6. Checked the accuracy of different algorithms. Comparing the accuracy scores among Logistic Regression , SVC, Decision Tree Classifier and Random Forest Classifier, Random Forest Classifier had highest value.
+   **MODELS USED**
+   
+   ##### Logistic Regression: 
+   ##### SVC: 
+   ##### Decision Tree Classifier:
+   ##### Random Forest Classifier:
+   
+   **LIBRARIES NEEDED**
+   
+   ##### Numpy, Pandas, Matplotlib, Seaborn, Sklearn
+   
+   **ACCURACIES**
+   
+   ##### Logistic Regression: 0.5833333333333334
+   ##### SVC: 0.5833333333333334
+   ##### Decision Tree Classifier: 0.5757575757575758
+   ##### Random Forest Classifier: 0.6893939393939394
+   
+   **CONCLUSION**
+   
+   ##### Comparing the accuracy scores among Logistic Regression , SVC, Decision Tree Classifier and Random Forest Classifier, Random Forest Classifier had highest value.
+   
+   **NAME**
+   ##### Mrunal Jambenal [Github](https://github.com/mrunal736) [Linkedin](https://www.linkedin.com/in/mrunal-jambenal-70922b206)
+