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[FreeCourseSite.com] Udemy - Deep Learning using Keras - Complete Compact Dummies Guide

Torrent Hash :
5c187fcd661342d47955f2c26aea19a8166d1773
Content Size :
5.49 GB
Date :
2021-08-25
Short Magnet :
Short Magnet
https://0mag.top/!npOMAg QR code
Files ( 81 )size
01 Course Introduction and Table of Contents/001 Course Introduction and Table of Contents.mp4255.18 MB
17 Step 2 and 3 EDA and Data Preparation/001 Step 2 and 3 EDA and Data Preparation - Part 1.mp4149.77 MB
52 Hyper Parameter Tuning/002 Hyper Parameter Tuning - Part 2.mp4125.61 MB
40 CNN Basics/001 CNN Basics.mp4125.52 MB
17 Step 2 and 3 EDA and Data Preparation/002 Step 2 and 3 EDA and Data Preparation - Part 2.mp4120.41 MB
19 Step 5 and 6 Compile and Fit Model/001 Step 5 and 6 Compile and Fit Model.mp4110.25 MB
45 Flowers Classification CNN - Training and Visualization/001 Flowers Classification CNN - Training and Visualization.mp4106.53 MB
56 VGG16 Transfer Learning Training Flowers Dataset/002 VGG16 Transfer Learning Training Flowers Dataset - part 2.mp4106.31 MB
38 Keras Directory Image Augmentation/001 Keras Directory Image Augmentation.mp4105.63 MB
37 Keras Single Image Augmentation/001 Keras Single Image Augmentation - Part 1.mp4104.04 MB
30 Step 2 - EDA and Data Visualization/001 Step 2 - EDA and Data Visualization.mp4101.08 MB
54 VGG16 and VGG19 prediction/001 VGG16 and VGG19 prediction - Part 1.mp4100.73 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.mp499.73 MB
39 Keras Data Frame Augmentation/001 Keras Data Frame Augmentation.mp499.1 MB
52 Hyper Parameter Tuning/001 Hyper Parameter Tuning - Part 1.mp497.98 MB
41 Stride Padding and Flattening Concepts of CNN/001 Stride Padding and Flattening Concepts of CNN.mp496.13 MB
53 Transfer Learning using Pretrained Models - VGG Introduction/001 Transfer Learning using Pretrained Models - VGG Introduction.mp495.91 MB
37 Keras Single Image Augmentation/002 Keras Single Image Augmentation - Part 2.mp495.03 MB
55 ResNet50 Prediction/001 ResNet50 Prediction.mp494.23 MB
42 Flowers CNN Image Classification Model - Fetch Load and Prepare Data/001 Flowers CNN Image Classification Model - Fetch Load and Prepare Data.mp492.3 MB
15 Popular Neural Network Types/001 Popular Neural Network Types.mp489.15 MB
44 Flowers Classification CNN - Defining the Model/002 Flowers Classification CNN - Defining the Model - Part 2.mp489.03 MB
14 Popular Optimizers/001 Popular Optimizers.mp488.35 MB
03 Introduction to Deep learning and Neural Networks/001 Introduction to Deep learning and Neural Networks.mp487.53 MB
13 Popular Types of Loss Functions/001 Popular Types of Loss Functions.mp486.75 MB
23 Step 1 - Fetch and Load Data/001 Step 1 - Fetch and Load Data.mp485.89 MB
04 Setting up Computer - Installing Anaconda/001 Setting up Computer - Installing Anaconda.mp485.57 MB
35 Digital Image Basics/001 Digital Image Basics.mp483.91 MB
20 Step 7 Visualize Training and Metrics/001 Step 7 Visualize Training and Metrics.mp483.53 MB
50 Flowers Classification CNN - Padding and Filter Optimization/001 Flowers Classification CNN - Padding and Filter Optimization.mp482.87 MB
12 Popular Types of Activation Functions/001 Popular Types of Activation Functions.mp479.19 MB
32 Step 4 - Compile Fit and Plot the Model/001 Step 4 - Compile Fit and Plot the Model.mp478.17 MB
56 VGG16 Transfer Learning Training Flowers Dataset/001 VGG16 Transfer Learning Training Flowers Dataset - part 1.mp476.67 MB
24 Step 2 and 3 - EDA and Data Preparation/002 Step 2 and 3 - EDA and Data Preparation - Part 2.mp476.19 MB
26 Step 5 - Compile Fit and Plot the Model/001 Step 5 - Compile Fit and Plot the Model.mp474.42 MB
31 Step 3 - Defining the Model/001 Step 3 - Defining the Model.mp472.82 MB
47 Flowers Classification CNN - Load Saved Model and Predict/001 Flowers Classification CNN - Load Saved Model and Predict.mp469.87 MB
49 Flowers Classification CNN - Dropout Regularization/001 Flowers Classification CNN - Dropout Regularization.mp469.36 MB
24 Step 2 and 3 - EDA and Data Preparation/001 Step 2 and 3 - EDA and Data Preparation - Part 1.mp469.1 MB
36 Basic Image Processing using Keras Functions/002 Basic Image Processing using Keras Functions - Part 2.mp465.45 MB
25 Step 4 - Defining the model/001 Step 4 - Defining the model.mp465.42 MB
18 Step 4 Defining the Keras Model/002 Step 4 Defining the Keras Model - Part 2.mp464.54 MB
43 Flowers Classification CNN - Create Test and Train Folders/001 Flowers Classification CNN - Create Test and Train Folders.mp463.93 MB
05 Python Basics/001 Python Basics - Assignment.mp463.43 MB
10 Basic Structure of Artificial Neuron and Neural Network/001 Basic Structure of Artificial Neuron and Neural Network.mp463 MB
36 Basic Image Processing using Keras Functions/001 Basic Image Processing using Keras Functions - Part 1.mp462.65 MB
08 Pandas Basics/001 Pandas Basics - Part 1.mp458.6 MB
51 Flowers Classification CNN - Augmentation Optimization/001 Flowers Classification CNN - Augmentation Optimization.mp458.59 MB
18 Step 4 Defining the Keras Model/001 Step 4 Defining the Keras Model - Part 1.mp458.17 MB
05 Python Basics/005 Python Basics - Dictionary and Functions - part 1.mp453.6 MB

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