Update README.md

Author: bansalkanav

Module 4 - Machine Learning/01. Data Preparation and Modelling with sklearn/README.md

@@ -4,27 +4,27 @@
 <summary><h3>Types of Machine Learning</h3></summary>
 <ol>
 <li><details>
-<summary><h5>Supervised Learning</h5></summary>
+<summary><h4>Supervised Learning</h4></summary>
 <ul>
 <li>Classification Task</li>
 <li>Regression Task</li>
 </ul>
-<details>
-<summary><h5>Click here to view all the algorithms:</h5></summary>
-| Approach | Classification Algorithm | Regression Algorithm |
-| :---: | :---: | :---: |
-| Distance Based Approach | KNeighborsClassifier | KNeighborsRegressor |
-| Rule Based Approach | DecisionTreeClassifier | DecisionTreeRegressor |
-| Probability Based Approach | Naive Bayes | NA |
-| Boundary Based Approach | LogisticRegression and SVC | LinearRegression |
-| Ensemble Based Approach | RandomForestClassifier, GBDTClassifier, etc... | RandomForestRegressor, GBDTRegressor, etc... |
-| Deep Learning Based Approach | ANN for Classification | ANN for Regression |
-</details>
+<details>
+<summary><h5>Click here to view all the algorithms:</h5></summary>
+| Approach | Classification Algorithm | Regression Algorithm |
+| :---: | :---: | :---: |
+| Distance Based Approach | KNeighborsClassifier | KNeighborsRegressor |
+| Rule Based Approach | DecisionTreeClassifier | DecisionTreeRegressor |
+| Probability Based Approach | Naive Bayes | NA |
+| Boundary Based Approach | LogisticRegression and SVC | LinearRegression |
+| Ensemble Based Approach | RandomForestClassifier, GBDTClassifier, etc... | RandomForestRegressor, GBDTRegressor, etc... |
+| Deep Learning Based Approach | ANN for Classification | ANN for Regression |
+</details>
 </details></li>
 <li><details>
-<summary><h5>Unsupervised Learning</h5></summary>
+<summary><h4>Unsupervised Learning</h4></summary>
 </details></li>
-<li><h5>Reinforcement Learning</h5></li>
+<li><h4>Reinforcement Learning</h4></li>
 </ol>
 </details>