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文档列表

01 Course Introduction and Table of Contents/001 Course Introduction and Table of Contents.mp4 267.6 MB
17 Step 2 and 3 EDA and Data Preparation/001 Step 2 and 3 EDA and Data Preparation - Part 1.mp4 157.0 MB
52 Hyper Parameter Tuning/002 Hyper Parameter Tuning - Part 2.mp4 131.7 MB
40 CNN Basics/001 CNN Basics.mp4 131.6 MB
17 Step 2 and 3 EDA and Data Preparation/002 Step 2 and 3 EDA and Data Preparation - Part 2.mp4 126.3 MB
19 Step 5 and 6 Compile and Fit Model/001 Step 5 and 6 Compile and Fit Model.mp4 115.6 MB
45 Flowers Classification CNN - Training and Visualization/001 Flowers Classification CNN - Training and Visualization.mp4 111.7 MB
56 VGG16 Transfer Learning Training Flowers Dataset/002 VGG16 Transfer Learning Training Flowers Dataset - part 2.mp4 111.5 MB
38 Keras Directory Image Augmentation/001 Keras Directory Image Augmentation.mp4 110.8 MB
37 Keras Single Image Augmentation/001 Keras Single Image Augmentation - Part 1.mp4 109.1 MB
30 Step 2 - EDA and Data Visualization/001 Step 2 - EDA and Data Visualization.mp4 106.0 MB
54 VGG16 and VGG19 prediction/001 VGG16 and VGG19 prediction - Part 1.mp4 105.6 MB
16 King County House Sales Regression Model - Step 1 Fetch and Load Dataset/001 King County House Sales Regression Model - Step 1 Fetch and Load Dataset.mp4 104.6 MB
39 Keras Data Frame Augmentation/001 Keras Data Frame Augmentation.mp4 103.9 MB
52 Hyper Parameter Tuning/001 Hyper Parameter Tuning - Part 1.mp4 102.7 MB
41 Stride Padding and Flattening Concepts of CNN/001 Stride Padding and Flattening Concepts of CNN.mp4 100.8 MB
53 Transfer Learning using Pretrained Models - VGG Introduction/001 Transfer Learning using Pretrained Models - VGG Introduction.mp4 100.6 MB
37 Keras Single Image Augmentation/002 Keras Single Image Augmentation - Part 2.mp4 99.7 MB
55 ResNet50 Prediction/001 ResNet50 Prediction.mp4 98.8 MB
42 Flowers CNN Image Classification Model - Fetch Load and Prepare Data/001 Flowers CNN Image Classification Model - Fetch Load and Prepare Data.mp4 96.8 MB
15 Popular Neural Network Types/001 Popular Neural Network Types.mp4 93.5 MB
44 Flowers Classification CNN - Defining the Model/002 Flowers Classification CNN - Defining the Model - Part 2.mp4 93.4 MB
14 Popular Optimizers/001 Popular Optimizers.mp4 92.6 MB
03 Introduction to Deep learning and Neural Networks/001 Introduction to Deep learning and Neural Networks.mp4 91.8 MB
13 Popular Types of Loss Functions/001 Popular Types of Loss Functions.mp4 91.0 MB
23 Step 1 - Fetch and Load Data/001 Step 1 - Fetch and Load Data.mp4 90.1 MB
04 Setting up Computer - Installing Anaconda/001 Setting up Computer - Installing Anaconda.mp4 89.7 MB
35 Digital Image Basics/001 Digital Image Basics.mp4 88.0 MB
20 Step 7 Visualize Training and Metrics/001 Step 7 Visualize Training and Metrics.mp4 87.6 MB
50 Flowers Classification CNN - Padding and Filter Optimization/001 Flowers Classification CNN - Padding and Filter Optimization.mp4 86.9 MB
12 Popular Types of Activation Functions/001 Popular Types of Activation Functions.mp4 83.0 MB
32 Step 4 - Compile Fit and Plot the Model/001 Step 4 - Compile Fit and Plot the Model.mp4 82.0 MB
56 VGG16 Transfer Learning Training Flowers Dataset/001 VGG16 Transfer Learning Training Flowers Dataset - part 1.mp4 80.4 MB
24 Step 2 and 3 - EDA and Data Preparation/002 Step 2 and 3 - EDA and Data Preparation - Part 2.mp4 79.9 MB
26 Step 5 - Compile Fit and Plot the Model/001 Step 5 - Compile Fit and Plot the Model.mp4 78.0 MB
31 Step 3 - Defining the Model/001 Step 3 - Defining the Model.mp4 76.4 MB
47 Flowers Classification CNN - Load Saved Model and Predict/001 Flowers Classification CNN - Load Saved Model and Predict.mp4 73.3 MB
49 Flowers Classification CNN - Dropout Regularization/001 Flowers Classification CNN - Dropout Regularization.mp4 72.7 MB
24 Step 2 and 3 - EDA and Data Preparation/001 Step 2 and 3 - EDA and Data Preparation - Part 1.mp4 72.5 MB
36 Basic Image Processing using Keras Functions/002 Basic Image Processing using Keras Functions - Part 2.mp4 68.6 MB
25 Step 4 - Defining the model/001 Step 4 - Defining the model.mp4 68.6 MB
18 Step 4 Defining the Keras Model/002 Step 4 Defining the Keras Model - Part 2.mp4 67.7 MB
43 Flowers Classification CNN - Create Test and Train Folders/001 Flowers Classification CNN - Create Test and Train Folders.mp4 67.0 MB
05 Python Basics/001 Python Basics - Assignment.mp4 66.5 MB
10 Basic Structure of Artificial Neuron and Neural Network/001 Basic Structure of Artificial Neuron and Neural Network.mp4 66.1 MB
36 Basic Image Processing using Keras Functions/001 Basic Image Processing using Keras Functions - Part 1.mp4 65.7 MB
08 Pandas Basics/001 Pandas Basics - Part 1.mp4 61.4 MB
51 Flowers Classification CNN - Augmentation Optimization/001 Flowers Classification CNN - Augmentation Optimization.mp4 61.4 MB
18 Step 4 Defining the Keras Model/001 Step 4 Defining the Keras Model - Part 1.mp4 61.0 MB
05 Python Basics/005 Python Basics - Dictionary and Functions - part 1.mp4 56.2 MB
44 Flowers Classification CNN - Defining the Model/001 Flowers Classification CNN - Defining the Model - Part 1.mp4 56.2 MB
22 Heart Disease Binary Classification Model - Introduction/001 Heart Disease Binary Classification Model - Introduction.mp4 55.6 MB
09 Installing Deep Learning Libraries/001 Installing Deep Learning Libraries.mp4 55.4 MB
06 Numpy Basics/002 Numpy Basics - Part 2.mp4 55.3 MB
07 Matplotlib Basics/001 Matplotlib Basics - part 1.mp4 53.7 MB
27 Step 5 - Predicting Heart Disease using Model/001 Step 5 - Predicting Heart Disease using Model.mp4 52.5 MB
11 Activation Functions Introduction/001 Activation Functions Introduction.mp4 51.7 MB
34 Serialize and Save Trained Model for Later Use/001 Serialize and Save Trained Model for Later Use.mp4 51.5 MB
21 Step 8 Prediction Using the Model/001 Step 8 Prediction Using the Model.mp4 50.5 MB
02 Introduction to AI and Machine Learning/001 Introduction to AI and Machine Learning.mp4 49.8 MB
05 Python Basics/002 Python Basics - Flow Control - Part 1.mp4 49.1 MB
54 VGG16 and VGG19 prediction/002 VGG16 and VGG19 prediction - Part 2.mp4 48.8 MB
36 Basic Image Processing using Keras Functions/003 Basic Image Processing using Keras Functions - Part 3.mp4 48.7 MB
05 Python Basics/004 Python Basics - List and Tuples.mp4 48.3 MB
29 Step1 - Fetch and Load Data/001 Step1 - Fetch and Load Data.mp4 48.2 MB
33 Step 5 - Predicting Wine Quality using Model/001 Step 5 - Predicting Wine Quality using Model.mp4 44.1 MB
06 Numpy Basics/001 Numpy Basics - Part 1.mp4 43.0 MB
48 Flowers Classification CNN - Optimization Techniques - Introduction/001 Flowers Classification CNN - Optimization Techniques - Introduction.mp4 42.5 MB
07 Matplotlib Basics/002 Matplotlib Basics - part 2.mp4 39.8 MB
28 Redwine Quality MultiClass Classification Model - Introduction/001 Redwine Quality MultiClass Classification Model - Introduction.mp4 38.9 MB
44 Flowers Classification CNN - Defining the Model/003 Flowers Classification CNN - Defining the Model - Part 3.mp4 38.6 MB
05 Python Basics/003 Python Basics - Flow Control - Part 2.mp4 38.2 MB
05 Python Basics/006 Python Basics - Dictionary and Functions - part 2.mp4 35.6 MB
08 Pandas Basics/002 Pandas Basics - Part 2.mp4 35.2 MB
57 VGG16 Transfer Learning Flower Prediction/001 VGG16 Transfer Learning Flower Prediction.mp4 28.8 MB
46 Flowers Classification CNN - Save Model for Later Use/001 Flowers Classification CNN - Save Model for Later Use.mp4 27.6 MB
58 SOURCE CODE AND FILES ATTACHED/001 SOURCE CODE AND FILES ATTACHED.html 1.1 kB
0. Websites you may like/[FCS Forum].url 133 Bytes
0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
0. Websites you may like/[CourseClub.ME].url 122 Bytes
0. Websites you may like/[GigaCourse.Com].url 49 Bytes

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