20.49 GB | 00:10:50 | mp4 | 1920X1080 | 16:9
Genre:eLearning |Language:English

Files Included :
1 Introduction (38.68 MB)
2 What is An Artificial Neuron (45.23 MB)
3 What is Deep Learning (48.02 MB)
4 Neural Network Basics (82.17 MB)
5 Convolutional Neural Networks (CNNs) (107.19 MB)
6 Natural Language Processing (NLP) (83.67 MB)
7 Challenge (26.75 MB)
1 Introduction (150.04 MB)
2 Binary to Multi-Class Classification EDA (85.44 MB)
3 Build, Compile, and Fit Model (54.25 MB)
4 Evaluate for Overfitting (plot curves) (106.46 MB)
5 Adjust HyperparametersData Augmentation (70.52 MB)
6 Repeat Until Happy with Results (159.24 MB)
1 Introduction (218.29 MB)
2 Kaggle Milestone Challenge Overview (176.68 MB)
3 Load Dataset with ImageDataGenerator (130.7 MB)
4 Challenge (33.57 MB)
5 Solution Video (107.86 MB)
1 Introduction (102.74 MB)
2 Explore Dataset and Clone Repo from CBTN GitHub (57.85 MB)
3 Prepare Train Dataset for Reduction (147.91 MB)
4 Reduce Train Dataset by 90% and Only Keep 10% (81.17 MB)
5 CHALLENGE (34.94 MB)
6 Solution (93.66 MB)
1 Introduction (144.92 MB)
10 Improved Learning Rate (9.28 MB)
2 Review Reduced Food 10 Dataset (10%) (41.27 MB)
3 Custom Callbacks (67.96 MB)
4 TensorBoard Callbacks (45.75 MB)
5 Checkpoint Callbacks (29.68 MB)
6 Early Stopping Callbacks (48.35 MB)
7 Callback Lists (63.39 MB)
8 Challenge Introduction (24.8 MB)
9 Challenge Solution (66.8 MB)
1 Introduction (107.53 MB)
2 Review Transfer Learning, Feature Extraction, and Fine-Tuning (74.74 MB)
3 Review Food 10 Dataset (59.85 MB)
4 Exploring Pre-Trained Models (184.27 MB)
5 Apply Transfer Learning, Feature Extraction, and Fine-tuning (64.17 MB)
6 Challenge (49.09 MB)
7 Solution video (65.45 MB)
1 Introduction (127.07 MB)
2 Clone and Create Reduced Food 10 Dataset (133.83 MB)
3 Apply Data Augmentation (91.92 MB)
4 Create a custom function to build Keras models simply using URLs