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| 001 Bubble sort.mp4 |
19.28Мб |
| 001 Decision trees introduction.mp4 |
31.76Мб |
| 001 Final words.mp4 |
6.21Мб |
| 001 Graph theory.mp4 |
29.01Мб |
| 001 Installing LiClipse.mp4 |
11.77Мб |
| 001 Introduction.mp4 |
4.07Мб |
| 001 Introduction.mp4 |
22.06Мб |
| 001 Introduction.mp4 |
16.57Мб |
| 001 K-means clustering introduction.mp4 |
34.02Мб |
| 001 K-nearest neighbour introduction.mp4 |
37.32Мб |
| 001 Linear regression introduction.mp4 |
23.26Мб |
| 001 Linked List introduction.mp4 |
35.21Мб |
| 001 Red-black trees.mp4 |
60.22Мб |
| 002 Breadth-first search introduction.mp4 |
11.34Мб |
| 002 Complexity theory.mp4 |
56.85Мб |
| 002 Decision tree example I.mp4 |
5.82Мб |
| 002 Insertion sort.mp4 |
18.81Мб |
| 002 K-means clustering example.mp4 |
17.11Мб |
| 002 K-nearest neighbour introduction - normalize data.mp4 |
10.27Мб |
| 002 Linear regression example.mp4 |
21.57Мб |
| 002 Linked list implementation.mp4 |
60.70Мб |
| 002 Simple example - logical AND table.mp4 |
30.06Мб |
| 002 Splay trees.mp4 |
64.68Мб |
| 003 Binary search tree introduction.mp4 |
31.76Мб |
| 003 Breadth-first search implementation.mp4 |
23.30Мб |
| 003 Coloring problem.mp4 |
58.73Мб |
| 003 DBSCAN clustering introduction.mp4 |
25.57Мб |
| 003 Decision tree example II - iris data.mp4 |
49.55Мб |
| 003 K-nearest neighbour example I.mp4 |
8.62Мб |
| 003 Logistic regression introduction.mp4 |
43.02Мб |
| 003 Merge sort.mp4 |
17.86Мб |
| 003 Training a neural network.mp4 |
36.10Мб |
| 004 Backtracking - N queens problem.mp4 |
29.48Мб |
| 004 Binary search tree implementation - Node.mp4 |
50.26Мб |
| 004 Complex neural networks.mp4 |
34.83Мб |
| 004 Cross validation.mp4 |
19.95Мб |
| 004 Depth-first search introduction.mp4 |
9.02Мб |
| 004 Hierarchical clustering introduction.mp4 |
22.85Мб |
| 004 K-nearest neighbour example II.mp4 |
7.56Мб |
| 004 Pruning and bagging.mp4 |
14.46Мб |
| 004 Quicksort.mp4 |
18.96Мб |
| 005 Applications of neural networks.mp4 |
24.97Мб |
| 005 Binary Search Tree implementation final.mp4 |
31.74Мб |
| 005 Counting sort.mp4 |
18.74Мб |
| 005 Depth-first search implementation.mp4 |
17.94Мб |
| 005 Euler cycles - chinese postman problem.mp4 |
41.65Мб |
| 005 Hierarchical clustering example.mp4 |
13.58Мб |
| 005 Logistic regression example - sigmoid function.mp4 |
46.61Мб |
| 005 Naive bayesian classifier introduction.mp4 |
45.74Мб |
| 005 Random forest introduction.mp4 |
10.28Мб |
| 006 AVL trees introduction.mp4 |
61.02Мб |
| 006 Boosting.mp4 |
12.18Мб |
| 006 Deep learning.mp4 |
11.23Мб |
| 006 Logistic regression example II.mp4 |
16.21Мб |
| 006 Naive bayesian example.mp4 |
20.78Мб |
| 006 Radix sort.mp4 |
26.66Мб |
| 006 Shortest path introduction.mp4 |
37.99Мб |
| 007 AVL tree implementation I.mp4 |
40.81Мб |
| 007 Dijkstra algorithm.mp4 |
64.97Мб |
| 007 Logistic regression example III - credit scoring.mp4 |
51.42Мб |
| 007 Neural network example - XOR problem.mp4 |
25.12Мб |
| 007 Random forest example I.mp4 |
8.92Мб |
| 007 Support vector machine SVM introduction.mp4 |
19.53Мб |
| 008 AVL tree implementation II.mp4 |
76.34Мб |
| 008 Bellman-Ford algorithm introduction.mp4 |
13.05Мб |
| 008 Random forest example II - enhance credit scoring.mp4 |
8.89Мб |
| 008 Support vector machine example I.mp4 |
10.85Мб |
| 009 Bellman-Ford implementation.mp4 |
74.66Мб |
| 009 Heaps introduction.mp4 |
45.62Мб |
| 009 Support vector machine example II - image recognition.mp4 |
22.78Мб |
| 010 Heap implementation I.mp4 |
31.97Мб |
| 010 Spanning trees introduction.mp4 |
36.42Мб |
| 011 Heap implementation II - heapsort.mp4 |
37.81Мб |
| 011 Kruskal algorithm I - The union find data structure.mp4 |
67.70Мб |
| 012 Hashtable introduction.mp4 |
69.79Мб |
| 012 Kruskal algorithm II.mp4 |
27.90Мб |
| 013 Prims-Jarnik algorithm.mp4 |
45.20Мб |
| 013 Ternary search trees introduction.mp4 |
44.46Мб |
| 014 Ternary search trees implementation I.mp4 |
33.25Мб |
| 015 Ternary search trees implementation II.mp4 |
21.22Мб |