2.98 GB | 00:22:10 | mp4 | 1920X1080  | 16:9
Genre:eLearning |Language:English

Files Included :
1 - Introduction  (11.34 MB)
27 - Different ways to create ANN using Keras  (8.67 MB)
28 - Building the Neural Network using Keras  (77.49 MB)
29 - Compiling and Training the Neural Network model  (107.17 MB)
30 - Evaluating performance and Predicting using Keras  (90.7 MB)
31 - Building Neural Network for Regression Problem  (250.53 MB)
32 - Using Functional API for complex architectures  (119.79 MB)
33 - Saving Restoring Models and Using Callbacks  (245.61 MB)
34 - Hyperparameter Tuning  (44.45 MB)
35 - CNN Introduction  (32.01 MB)
36 - Stride  (10.58 MB)
37 - Padding  (20.03 MB)
38 - Filters and Feature maps  (40.26 MB)
39 - Channels  (113.57 MB)
40 - PoolingLayer  (25.28 MB)
41 - CNN model in Python Preprocessing  (51.82 MB)
42 - CNN model in Python structure and Compile  (33.81 MB)
43 - CNN model in Python Training and results  (70.18 MB)
44 - Comparison Pooling vs Without Pooling in Python  (95.63 MB)
45 - Project Introduction  (31.44 MB)
47 - Project Data Preprocessing in Python  (93.75 MB)
48 - Project Training CNN model in Python  (60.42 MB)
49 - Project in Python model results  (16.62 MB)
50 - Project Data Augmentation Preprocessing  (33.49 MB)
51 - Project Data Augmentation Training and Results  (47.36 MB)
10 - Working with Numpy Library of Python  (43.55 MB)
11 - Working with Pandas Library of Python  (55.88 MB)
12 - Working with Seaborn Library of Python  (37.76 MB)
3 - Installing Python and Anaconda  (13.28 MB)
4 - This is a milestone  (26.16 MB)
5 - Opening Jupyter Notebook  (88.41 MB)
6 - Introduction to Jupyter  (31.98 MB)
7 - Arithmetic operators in Python Python Basics  (10.41 MB)
8 - Strings in Python Python Basics  (81.09 MB)
9 - Lists Tuples and Directories Python Basics  (48.61 MB)
52 - ILSVRC  (13.66 MB)
53 - LeNET  (4.8 MB)
54 - VGG16NET  (6.79 MB)
55 - GoogLeNet  (11.96 MB)
56 - Transfer Learning  (19.7 MB)
57 - Project Transfer Learning VGG16  (204.52 MB)
59 - The final milestone  (8.36 MB)
13 - Integrating ChatGPT with Jupyter notebook  (52.36 MB)
14 - Perceptron  (30.65 MB)
15 - Activation Functions  (22.9 MB)
16 - Python Creating Perceptron model  (118.39 MB)
17 - Basic Terminologies  (26.87 MB)
18 - Gradient Descent  (41.51 MB)
19 - Back Propagation  (79.14 MB)
20 - Some Important Concepts  (49.19 MB)
21 - Hyperparameters  (30.75 MB)
22 - Keras and Tensorflow  (10.19 MB)
23 - Installing Tensorflow and Keras  (20.09 MB)
24 - Dataset for classification  (70.38 MB)
25 - Normalization and TestTrain split  (60.27 MB)
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