Machine Learning, Operating System, Data Structure, Algorithm

SVM II Support Vector Machine II Classification II Regression II Supervised Learning II ML II DL
48:17
SVM II Support Vector Machine II Classification II Regression II Supervised Learning II ML II DL
Hierarchical Clustering II Agglomerative Clustering II Unsupervised Learning II AI II ML II DL
24:02
Hierarchical Clustering II Agglomerative Clustering II Unsupervised Learning II AI II ML II DL
DBSCAN Clustering II Clustering II Unsupervised Learning II EPS II minPts II AI II ML II DL
23:18
DBSCAN Clustering II Clustering II Unsupervised Learning II EPS II minPts II AI II ML II DL
K-Means Clustering II Clustering II Unsupervised Learning II Centroid II AI II ML II DL
40:08
K-Means Clustering II Clustering II Unsupervised Learning II Centroid II AI II ML II DL
AVL Tree [Part-2] II Deletion II RR II LL II RL II LR II Rotation
21:05
AVL Tree [Part-2] II Deletion II RR II LL II RL II LR II Rotation
AVL Tree [Part-1] II Introduction II Insertion II RR II LL II RL II LR II Left and Right Rotation
59:02
AVL Tree [Part-1] II Introduction II Insertion II RR II LL II RL II LR II Left and Right Rotation
Ensemble Learning II Bagging II Boosting II Parallel Learning II Sequential Learning II Weight
35:55
Ensemble Learning II Bagging II Boosting II Parallel Learning II Sequential Learning II Weight
Shortest Path Algorithms II Floyd Warshall Algorithm II Single Source and All Pair SP Algorithm
53:59
Shortest Path Algorithms II Floyd Warshall Algorithm II Single Source and All Pair SP Algorithm
Shortest Path Algorithms [Part-02] II Bellman Ford Algorithm II Single Source All Pair Shortest Path
51:04
Shortest Path Algorithms [Part-02] II Bellman Ford Algorithm II Single Source All Pair Shortest Path
Shortest Path Algorithms [Part-01] II Dijkstra Algorithm II Single Source and All Pair Shortest Path
47:27
Shortest Path Algorithms [Part-01] II Dijkstra Algorithm II Single Source and All Pair Shortest Path
Hyperparameter Tunning [ Part-01 ] II Grid Search II Random Search II Cross-Validation II Parameters
36:10
Hyperparameter Tunning [ Part-01 ] II Grid Search II Random Search II Cross-Validation II Parameters
Minimum Spanning Tree II MST II Spanning Tree II Prims Algorithm II Kruskal Algorithm
32:01
Minimum Spanning Tree II MST II Spanning Tree II Prims Algorithm II Kruskal Algorithm
Edge Types in DFS Traversal II Graph II Tree Edge II Forward Edge II Backward Edge II Cross Edge
37:54
Edge Types in DFS Traversal II Graph II Tree Edge II Forward Edge II Backward Edge II Cross Edge
Performance Metric [Final] II Accuracy II Confusion Matrix II Precision II Recall II F1-Score II AUC
34:13
Performance Metric [Final] II Accuracy II Confusion Matrix II Precision II Recall II F1-Score II AUC
Graph II Introduction II Vertices II Edges II BFS II DFS II Adjacency Matrix II Adjacency List
47:17
Graph II Introduction II Vertices II Edges II BFS II DFS II Adjacency Matrix II Adjacency List
Performance Metrics [Part-02] II Evaluation of ML Algo II Regression and Classification Metrics
33:29
Performance Metrics [Part-02] II Evaluation of ML Algo II Regression and Classification Metrics
Binary Search Tree II BST II Creation II Traversal II Deletion II Construction of BST II Preorder
41:26
Binary Search Tree II BST II Creation II Traversal II Deletion II Construction of BST II Preorder
Binary Tree Traversal [Part-03] II Preorder II Postorder II Construction of Binary Tree
32:19
Binary Tree Traversal [Part-03] II Preorder II Postorder II Construction of Binary Tree
Performance Metrics [ Part-01 ] II Evaluation of ML Algo II Regression and Classification Metrics
30:32
Performance Metrics [ Part-01 ] II Evaluation of ML Algo II Regression and Classification Metrics
Covariance & Correlation II Feature Significance II Feature Selection II Covariance II Correlation
33:57
Covariance & Correlation II Feature Significance II Feature Selection II Covariance II Correlation
Binary Tree Traversal [Part-02] II Inorder II Postorder II Construction of Binary Tree
46:51
Binary Tree Traversal [Part-02] II Inorder II Postorder II Construction of Binary Tree
Hands-On Machine Learning Development [ Final ] II Scaling II Label Encoding II Model Development
39:54
Hands-On Machine Learning Development [ Final ] II Scaling II Label Encoding II Model Development
Binary Tree Traversal [Part-01] II InOrder II PreOrder II PostOrder II Recursion II Root
40:46
Binary Tree Traversal [Part-01] II InOrder II PreOrder II PostOrder II Recursion II Root
Binary Tree Implementation II Malloc() II Create() II Linked List II Root II Left II Right
42:00
Binary Tree Implementation II Malloc() II Create() II Linked List II Root II Left II Right
Hands-On Machine Learning Development [ Part - 02 ] II Data Acquiring II Data Loading II Exploration
37:59
Hands-On Machine Learning Development [ Part - 02 ] II Data Acquiring II Data Loading II Exploration
Binary Tree Representation II Array Representation II Linked List Representation II Root Pointer
39:33
Binary Tree Representation II Array Representation II Linked List Representation II Root Pointer
Binary Tree II Introduction II Types of BT II Full BT II Complete BT II Perfect BT II Degenerate BT
42:33
Binary Tree II Introduction II Types of BT II Full BT II Complete BT II Perfect BT II Degenerate BT
Tree Introduction II Root II Node II Leaf Node II Child Node II Parent Node II Path II Applications
41:36
Tree Introduction II Root II Node II Leaf Node II Child Node II Parent Node II Path II Applications
Hands-On Machine Learning Development [ Part - 01 ] II Data Acquiring II Loading II Exploration
39:09
Hands-On Machine Learning Development [ Part - 01 ] II Data Acquiring II Loading II Exploration
Data Preprocessing [ Part - 02 ] II Data Integration II Data Reduction II Data Quality Check
38:53
Data Preprocessing [ Part - 02 ] II Data Integration II Data Reduction II Data Quality Check