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[FreeCourseSite.com] Udemy - Deep Learning using Keras - Complete Compact Dummies Guide
magnet:?xt=urn:btih:5c187fcd661342d47955f2c26aea19a8166d1773&dn=[FreeCourseSite.com] Udemy - Deep Learning using Keras - Complete Compact Dummies Guide
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5c187fcd661342d47955f2c26aea19a8166d1773
infohash:
76
文件数量
5.49 GB
文件大小
2021-8-25 02:14
创建日期
2024-9-21 20:24
最后访问
相关分词
FreeCourseSite
com
Udemy
-
Deep
Learning
using
Keras
-
Complete
Compact
Dummies
Guide
01 Course Introduction and Table of Contents/001 Course Introduction and Table of Contents.mp4 255.18 MB
02 Introduction to AI and Machine Learning/001 Introduction to AI and Machine Learning.mp4 47.45 MB
03 Introduction to Deep learning and Neural Networks/001 Introduction to Deep learning and Neural Networks.mp4 87.53 MB
04 Setting up Computer - Installing Anaconda/001 Setting up Computer - Installing Anaconda.mp4 85.57 MB
05 Python Basics/001 Python Basics - Assignment.mp4 63.43 MB
05 Python Basics/002 Python Basics - Flow Control - Part 1.mp4 46.83 MB
05 Python Basics/003 Python Basics - Flow Control - Part 2.mp4 36.43 MB
05 Python Basics/004 Python Basics - List and Tuples.mp4 46.08 MB
05 Python Basics/005 Python Basics - Dictionary and Functions - part 1.mp4 53.6 MB
05 Python Basics/006 Python Basics - Dictionary and Functions - part 2.mp4 33.93 MB
06 Numpy Basics/001 Numpy Basics - Part 1.mp4 41.01 MB
06 Numpy Basics/002 Numpy Basics - Part 2.mp4 52.78 MB
07 Matplotlib Basics/001 Matplotlib Basics - part 1.mp4 51.23 MB
07 Matplotlib Basics/002 Matplotlib Basics - part 2.mp4 37.99 MB
08 Pandas Basics/001 Pandas Basics - Part 1.mp4 58.6 MB
08 Pandas Basics/002 Pandas Basics - Part 2.mp4 33.57 MB
09 Installing Deep Learning Libraries/001 Installing Deep Learning Libraries.mp4 52.79 MB
10 Basic Structure of Artificial Neuron and Neural Network/001 Basic Structure of Artificial Neuron and Neural Network.mp4 63 MB
11 Activation Functions Introduction/001 Activation Functions Introduction.mp4 49.3 MB
12 Popular Types of Activation Functions/001 Popular Types of Activation Functions.mp4 79.19 MB
13 Popular Types of Loss Functions/001 Popular Types of Loss Functions.mp4 86.75 MB
14 Popular Optimizers/001 Popular Optimizers.mp4 88.35 MB
15 Popular Neural Network Types/001 Popular Neural Network Types.mp4 89.15 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 99.73 MB
17 Step 2 and 3 EDA and Data Preparation/001 Step 2 and 3 EDA and Data Preparation - Part 1.mp4 149.77 MB
17 Step 2 and 3 EDA and Data Preparation/002 Step 2 and 3 EDA and Data Preparation - Part 2.mp4 120.41 MB
18 Step 4 Defining the Keras Model/001 Step 4 Defining the Keras Model - Part 1.mp4 58.17 MB
18 Step 4 Defining the Keras Model/002 Step 4 Defining the Keras Model - Part 2.mp4 64.54 MB
19 Step 5 and 6 Compile and Fit Model/001 Step 5 and 6 Compile and Fit Model.mp4 110.25 MB
20 Step 7 Visualize Training and Metrics/001 Step 7 Visualize Training and Metrics.mp4 83.53 MB
21 Step 8 Prediction Using the Model/001 Step 8 Prediction Using the Model.mp4 48.13 MB
22 Heart Disease Binary Classification Model - Introduction/001 Heart Disease Binary Classification Model - Introduction.mp4 53.05 MB
23 Step 1 - Fetch and Load Data/001 Step 1 - Fetch and Load Data.mp4 85.89 MB
24 Step 2 and 3 - EDA and Data Preparation/001 Step 2 and 3 - EDA and Data Preparation - Part 1.mp4 69.1 MB
24 Step 2 and 3 - EDA and Data Preparation/002 Step 2 and 3 - EDA and Data Preparation - Part 2.mp4 76.19 MB
25 Step 4 - Defining the model/001 Step 4 - Defining the model.mp4 65.42 MB
26 Step 5 - Compile Fit and Plot the Model/001 Step 5 - Compile Fit and Plot the Model.mp4 74.42 MB
27 Step 5 - Predicting Heart Disease using Model/001 Step 5 - Predicting Heart Disease using Model.mp4 50.06 MB
28 Redwine Quality MultiClass Classification Model - Introduction/001 Redwine Quality MultiClass Classification Model - Introduction.mp4 37.11 MB
29 Step1 - Fetch and Load Data/001 Step1 - Fetch and Load Data.mp4 46.01 MB
30 Step 2 - EDA and Data Visualization/001 Step 2 - EDA and Data Visualization.mp4 101.08 MB
31 Step 3 - Defining the Model/001 Step 3 - Defining the Model.mp4 72.82 MB
32 Step 4 - Compile Fit and Plot the Model/001 Step 4 - Compile Fit and Plot the Model.mp4 78.17 MB
33 Step 5 - Predicting Wine Quality using Model/001 Step 5 - Predicting Wine Quality using Model.mp4 42.02 MB
34 Serialize and Save Trained Model for Later Use/001 Serialize and Save Trained Model for Later Use.mp4 49.14 MB
35 Digital Image Basics/001 Digital Image Basics.mp4 83.91 MB
36 Basic Image Processing using Keras Functions/001 Basic Image Processing using Keras Functions - Part 1.mp4 62.65 MB
36 Basic Image Processing using Keras Functions/002 Basic Image Processing using Keras Functions - Part 2.mp4 65.45 MB
36 Basic Image Processing using Keras Functions/003 Basic Image Processing using Keras Functions - Part 3.mp4 46.44 MB
37 Keras Single Image Augmentation/001 Keras Single Image Augmentation - Part 1.mp4 104.04 MB
37 Keras Single Image Augmentation/002 Keras Single Image Augmentation - Part 2.mp4 95.03 MB
38 Keras Directory Image Augmentation/001 Keras Directory Image Augmentation.mp4 105.63 MB
39 Keras Data Frame Augmentation/001 Keras Data Frame Augmentation.mp4 99.1 MB
40 CNN Basics/001 CNN Basics.mp4 125.52 MB
41 Stride Padding and Flattening Concepts of CNN/001 Stride Padding and Flattening Concepts of CNN.mp4 96.13 MB
42 Flowers CNN Image Classification Model - Fetch Load and Prepare Data/001 Flowers CNN Image Classification Model - Fetch Load and Prepare Data.mp4 92.3 MB
43 Flowers Classification CNN - Create Test and Train Folders/001 Flowers Classification CNN - Create Test and Train Folders.mp4 63.93 MB
44 Flowers Classification CNN - Defining the Model/001 Flowers Classification CNN - Defining the Model - Part 1.mp4 53.57 MB
44 Flowers Classification CNN - Defining the Model/002 Flowers Classification CNN - Defining the Model - Part 2.mp4 89.03 MB
44 Flowers Classification CNN - Defining the Model/003 Flowers Classification CNN - Defining the Model - Part 3.mp4 36.79 MB
45 Flowers Classification CNN - Training and Visualization/001 Flowers Classification CNN - Training and Visualization.mp4 106.53 MB
46 Flowers Classification CNN - Save Model for Later Use/001 Flowers Classification CNN - Save Model for Later Use.mp4 26.35 MB
47 Flowers Classification CNN - Load Saved Model and Predict/001 Flowers Classification CNN - Load Saved Model and Predict.mp4 69.87 MB
48 Flowers Classification CNN - Optimization Techniques - Introduction/001 Flowers Classification CNN - Optimization Techniques - Introduction.mp4 40.54 MB
49 Flowers Classification CNN - Dropout Regularization/001 Flowers Classification CNN - Dropout Regularization.mp4 69.36 MB
50 Flowers Classification CNN - Padding and Filter Optimization/001 Flowers Classification CNN - Padding and Filter Optimization.mp4 82.87 MB
51 Flowers Classification CNN - Augmentation Optimization/001 Flowers Classification CNN - Augmentation Optimization.mp4 58.59 MB
52 Hyper Parameter Tuning/001 Hyper Parameter Tuning - Part 1.mp4 97.98 MB
52 Hyper Parameter Tuning/002 Hyper Parameter Tuning - Part 2.mp4 125.61 MB
53 Transfer Learning using Pretrained Models - VGG Introduction/001 Transfer Learning using Pretrained Models - VGG Introduction.mp4 95.91 MB
54 VGG16 and VGG19 prediction/001 VGG16 and VGG19 prediction - Part 1.mp4 100.73 MB
54 VGG16 and VGG19 prediction/002 VGG16 and VGG19 prediction - Part 2.mp4 46.51 MB
55 ResNet50 Prediction/001 ResNet50 Prediction.mp4 94.23 MB
56 VGG16 Transfer Learning Training Flowers Dataset/001 VGG16 Transfer Learning Training Flowers Dataset - part 1.mp4 76.67 MB
56 VGG16 Transfer Learning Training Flowers Dataset/002 VGG16 Transfer Learning Training Flowers Dataset - part 2.mp4 106.31 MB
57 VGG16 Transfer Learning Flower Prediction/001 VGG16 Transfer Learning Flower Prediction.mp4 27.48 MB
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