|
|
0
|
|
833.9 KB
|
|
|
001 Activation Functions Introduction.mp4
|
MP4
|
49.3 MB
|
|
|
001 Basic Image Processing using Keras Functions - Part 1.mp4
|
MP4
|
62.7 MB
|
|
|
001 Basic Structure of Artificial Neuron and Neural Network.mp4
|
MP4
|
63 MB
|
|
|
001 CNN Basics.mp4
|
MP4
|
125.5 MB
|
|
|
001 Course Introduction and Table of Contents.mp4
|
MP4
|
255.2 MB
|
|
|
001 Flowers CNN Image Classification Model - Fetch Load and Prepare Data.mp4
|
MP4
|
92.3 MB
|
|
|
001 Flowers Classification CNN - Augmentation Optimization.mp4
|
MP4
|
58.6 MB
|
|
|
001 Flowers Classification CNN - Create Test and Train Folders.mp4
|
MP4
|
63.9 MB
|
|
|
001 Flowers Classification CNN - Dropout Regularization.mp4
|
MP4
|
69.4 MB
|
|
|
001 Flowers Classification CNN - Load Saved Model and Predict.mp4
|
MP4
|
69.9 MB
|
|
|
001 Flowers Classification CNN - Save Model for Later Use.mp4
|
MP4
|
26.4 MB
|
|
|
001 Flowers Classification CNN - Training and Visualization.mp4
|
MP4
|
106.5 MB
|
|
|
001 Heart Disease Binary Classification Model - Introduction.mp4
|
MP4
|
53 MB
|
|
|
001 Hyper Parameter Tuning - Part 1.mp4
|
MP4
|
98 MB
|
|
|
001 Installing Deep Learning Libraries.mp4
|
MP4
|
52.8 MB
|
|
|
1
|
|
233.4 KB
|
|
|
001 Digital Image Basics.mp4
|
MP4
|
83.9 MB
|
|
|
001 Flowers Classification CNN - Defining the Model - Part 1.mp4
|
MP4
|
53.6 MB
|
|
|
001 Flowers Classification CNN - Optimization Techniques - Introduction.mp4
|
MP4
|
40.5 MB
|
|
|
001 Flowers Classification CNN - Padding and Filter Optimization.mp4
|
MP4
|
82.9 MB
|
|
|
001 Introduction to AI and Machine Learning.mp4
|
MP4
|
47.4 MB
|
|
|
001 Introduction to Deep learning and Neural Networks.mp4
|
MP4
|
87.5 MB
|
|
|
001 Keras Data Frame Augmentation.mp4
|
MP4
|
99.1 MB
|
|
|
001 Keras Directory Image Augmentation.mp4
|
MP4
|
105.6 MB
|
|
|
001 Keras Single Image Augmentation - Part 1.mp4
|
MP4
|
104 MB
|
|
|
001 King County House Sales Regression Model - Step 1 Fetch and Load Dataset.mp4
|
MP4
|
99.7 MB
|
|
|
001 Matplotlib Basics - part 1.mp4
|
MP4
|
51.2 MB
|
|
|
001 Numpy Basics - Part 1.mp4
|
MP4
|
41 MB
|
|
|
001 Pandas Basics - Part 1.mp4
|
MP4
|
58.6 MB
|
|
|
001 Popular Neural Network Types.mp4
|
MP4
|
89.1 MB
|
|
|
001 Popular Optimizers.mp4
|
MP4
|
88.4 MB
|
|
|
001 Popular Types of Activation Functions.mp4
|
MP4
|
79.2 MB
|
|
|
001 Popular Types of Loss Functions.mp4
|
MP4
|
86.8 MB
|
|
|
001 Python Basics - Assignment.mp4
|
MP4
|
63.4 MB
|
|
|
001 Redwine Quality MultiClass Classification Model - Introduction.mp4
|
MP4
|
37.1 MB
|
|
|
001 ResNet50 Prediction.mp4
|
MP4
|
94.2 MB
|
|
|
001 SOURCE CODE AND FILES ATTACHED.html
|
HTML
|
1.1 KB
|
|
|
001 Serialize and Save Trained Model for Later Use.mp4
|
MP4
|
49.1 MB
|
|
|
001 Setting up Computer - Installing Anaconda.mp4
|
MP4
|
85.6 MB
|
|
|
001 Step 1 - Fetch and Load Data.mp4
|
MP4
|
85.9 MB
|
|
|
001 Step 2 - EDA and Data Visualization.mp4
|
MP4
|
101.1 MB
|
|
|
001 Step 2 and 3 - EDA and Data Preparation - Part 1.mp4
|
MP4
|
69.1 MB
|
|
|
001 Step 2 and 3 EDA and Data Preparation - Part 1.mp4
|
MP4
|
149.8 MB
|
|
|
001 Step 3 - Defining the Model.mp4
|
MP4
|
72.8 MB
|
|
|
001 Step 4 - Compile Fit and Plot the Model.mp4
|
MP4
|
78.2 MB
|
|
|
001 Step 4 - Defining the model.mp4
|
MP4
|
65.4 MB
|
|
|
001 Step 4 Defining the Keras Model - Part 1.mp4
|
MP4
|
58.2 MB
|
|
|
001 Step 5 - Compile Fit and Plot the Model.mp4
|
MP4
|
74.4 MB
|
|
|
001 Step 5 - Predicting Heart Disease using Model.mp4
|
MP4
|
50.1 MB
|
|
|
001 Step 5 - Predicting Wine Quality using Model.mp4
|
MP4
|
42 MB
|
|
|
001 Step 5 and 6 Compile and Fit Model.mp4
|
MP4
|
110.2 MB
|
|
|
001 Step 7 Visualize Training and Metrics.mp4
|
MP4
|
83.5 MB
|
|
|
001 Step 8 Prediction Using the Model.mp4
|
MP4
|
48.1 MB
|
|
|
001 Step1 - Fetch and Load Data.mp4
|
MP4
|
46 MB
|
|
|
001 Stride Padding and Flattening Concepts of CNN.mp4
|
MP4
|
96.1 MB
|
|
|
001 Transfer Learning using Pretrained Models - VGG Introduction.mp4
|
MP4
|
95.9 MB
|
|
|
001 VGG16 Transfer Learning Flower Prediction.mp4
|
MP4
|
27.5 MB
|
|
|
001 VGG16 Transfer Learning Training Flowers Dataset - part 1.mp4
|
MP4
|
76.7 MB
|
|
|
001 VGG16 and VGG19 prediction - Part 1.mp4
|
MP4
|
100.7 MB
|
|
|
002 Flowers Classification CNN - Defining the Model - Part 2.mp4
|
MP4
|
89 MB
|
|
|
002 Hyper Parameter Tuning - Part 2.mp4
|
MP4
|
125.6 MB
|
|
|
002 Keras Single Image Augmentation - Part 2.mp4
|
MP4
|
95 MB
|
|
|
002 Pandas Basics - Part 2.mp4
|
MP4
|
33.6 MB
|
|
|
002 Step 2 and 3 EDA and Data Preparation - Part 2.mp4
|
MP4
|
120.4 MB
|
|
|
002 VGG16 Transfer Learning Training Flowers Dataset - part 2.mp4
|
MP4
|
106.3 MB
|
|
|
002 VGG16 and VGG19 prediction - Part 2.mp4
|
MP4
|
46.5 MB
|
|
|
TutsNode.com.txt
|
TXT
|
102.4 B
|
|
|
[TGx]Downloaded from torrentgalaxy.to .txt
|
TXT
|
614.4 B
|
|
|
2
|
|
395.9 KB
|
|
|
002 Basic Image Processing using Keras Functions - Part 2.mp4
|
MP4
|
65.4 MB
|
|
|
002 Matplotlib Basics - part 2.mp4
|
MP4
|
38 MB
|
|
|
002 Numpy Basics - Part 2.mp4
|
MP4
|
52.8 MB
|
|
|
002 Python Basics - Flow Control - Part 1.mp4
|
MP4
|
46.8 MB
|
|
|
002 Step 2 and 3 - EDA and Data Preparation - Part 2.mp4
|
MP4
|
76.2 MB
|
|
|
002 Step 4 Defining the Keras Model - Part 2.mp4
|
MP4
|
64.5 MB
|
|
|
003 Basic Image Processing using Keras Functions - Part 3.mp4
|
MP4
|
46.4 MB
|
|
|
3
|
|
496.5 KB
|
|
|
003 Flowers Classification CNN - Defining the Model - Part 3.mp4
|
MP4
|
36.8 MB
|
|
|
003 Python Basics - Flow Control - Part 2.mp4
|
MP4
|
36.4 MB
|
|
|
004 Python Basics - List and Tuples.mp4
|
MP4
|
46.1 MB
|
|
|
4
|
|
602.8 KB
|
|
|
005 Python Basics - Dictionary and Functions - part 1.mp4
|
MP4
|
53.6 MB
|
|
|
5
|
|
769 KB
|
|
|
006 Python Basics - Dictionary and Functions - part 2.mp4
|
MP4
|
33.9 MB
|
|
|
6
|
|
479.4 KB
|
|
|
7
|
|
705.4 KB
|
|
|
8
|
|
379.3 KB
|
|
|
9
|
|
983.7 KB
|
|
|
10
|
|
947.2 KB
|
|
|
11
|
|
278.8 KB
|
|
|
12
|
|
274.6 KB
|
|
|
13
|
|
924.6 KB
|
|
|
14
|
|
17.9 KB
|
|
|
15
|
|
895.4 KB
|
|
|
16
|
|
91.8 KB
|
|
|
17
|
|
989 KB
|
|
|
18
|
|
790.4 KB
|
|
|
19
|
|
715 KB
|
|
|
20
|
|
871.9 KB
|
|
|
21
|
|
988.3 KB
|
|
|
22
|
|
663.9 KB
|
|
|
23
|
|
483.6 KB
|
|
|
24
|
|
252.9 KB
|
|
|
25
|
|
107.8 KB
|
|
|
26
|
|
443.9 KB
|
|
|
27
|
|
92 KB
|
|
|
28
|
|
477.2 KB
|
|
|
29
|
|
131.5 KB
|
|
|
30
|
|
824.7 KB
|
|
|
31
|
|
854.7 KB
|
|
|
32
|
|
338.9 KB
|
|
|
33
|
|
824.8 KB
|
|
|
34
|
|
592.2 KB
|
|
|
35
|
|
184.4 KB
|
|
|
36
|
|
128.4 KB
|
|
|
37
|
|
651.7 KB
|
|
|
38
|
|
920.8 KB
|
|
|
39
|
|
566 KB
|
|
|
40
|
|
592.1 KB
|
|
|
41
|
|
476.1 KB
|
|
|
42
|
|
72.6 KB
|
|
|
43
|
|
584 KB
|
|
|
44
|
|
716.8 B
|
|
|
45
|
|
354.1 KB
|
|
|
46
|
|
408.4 KB
|
|
|
47
|
|
416.4 KB
|
|
|
48
|
|
850.2 KB
|
|
|
49
|
|
407.9 KB
|
|
|
50
|
|
435.3 KB
|
|
|
51
|
|
975.3 KB
|
|
|
52
|
|
219.2 KB
|
|
|
53
|
|
229.4 KB
|
|
|
54
|
|
785 KB
|
|
|
55
|
|
960.5 KB
|
|
|
56
|
|
715.5 KB
|
|
|
57
|
|
878.2 KB
|
|
|
58
|
|
886.1 KB
|
|
|
59
|
|
566.3 KB
|
|
|
60
|
|
175.5 KB
|
|
|
61
|
|
506.7 KB
|
|
|
62
|
|
576 KB
|
|
|
63
|
|
943.9 KB
|
|
|
67
|
|
468 KB
|
|
|
68
|
|
7.1 KB
|
|
|
69
|
|
908.7 KB
|
|
|
70
|
|
219 KB
|
|
|
71
|
|
582.7 KB
|
|
|
72
|
|
75.4 KB
|
|
|
73
|
|
440 KB
|
|
|
74
|
|
532.7 KB
|
