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| [TGx]Downloaded from torrentgalaxy.to .txt |
585б |
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| 001 Activation Functions Introduction.mp4 |
49.30Мб |
| 001 Basic Image Processing using Keras Functions - Part 1.mp4 |
62.65Мб |
| 001 Basic Structure of Artificial Neuron and Neural Network.mp4 |
63.00Мб |
| 001 CNN Basics.mp4 |
125.52Мб |
| 001 Course Introduction and Table of Contents.mp4 |
255.18Мб |
| 001 Digital Image Basics.mp4 |
83.91Мб |
| 001 Flowers Classification CNN - Augmentation Optimization.mp4 |
58.59Мб |
| 001 Flowers Classification CNN - Create Test and Train Folders.mp4 |
63.93Мб |
| 001 Flowers Classification CNN - Defining the Model - Part 1.mp4 |
53.57Мб |
| 001 Flowers Classification CNN - Dropout Regularization.mp4 |
69.36Мб |
| 001 Flowers Classification CNN - Load Saved Model and Predict.mp4 |
69.87Мб |
| 001 Flowers Classification CNN - Optimization Techniques - Introduction.mp4 |
40.54Мб |
| 001 Flowers Classification CNN - Padding and Filter Optimization.mp4 |
82.87Мб |
| 001 Flowers Classification CNN - Save Model for Later Use.mp4 |
26.35Мб |
| 001 Flowers Classification CNN - Training and Visualization.mp4 |
106.53Мб |
| 001 Flowers CNN Image Classification Model - Fetch Load and Prepare Data.mp4 |
92.30Мб |
| 001 Heart Disease Binary Classification Model - Introduction.mp4 |
53.05Мб |
| 001 Hyper Parameter Tuning - Part 1.mp4 |
97.98Мб |
| 001 Installing Deep Learning Libraries.mp4 |
52.79Мб |
| 001 Introduction to AI and Machine Learning.mp4 |
47.45Мб |
| 001 Introduction to Deep learning and Neural Networks.mp4 |
87.53Мб |
| 001 Keras Data Frame Augmentation.mp4 |
99.10Мб |
| 001 Keras Directory Image Augmentation.mp4 |
105.63Мб |
| 001 Keras Single Image Augmentation - Part 1.mp4 |
104.04Мб |
| 001 King County House Sales Regression Model - Step 1 Fetch and Load Dataset.mp4 |
99.73Мб |
| 001 Matplotlib Basics - part 1.mp4 |
51.23Мб |
| 001 Numpy Basics - Part 1.mp4 |
41.01Мб |
| 001 Pandas Basics - Part 1.mp4 |
58.60Мб |
| 001 Popular Neural Network Types.mp4 |
89.15Мб |
| 001 Popular Optimizers.mp4 |
88.35Мб |
| 001 Popular Types of Activation Functions.mp4 |
79.19Мб |
| 001 Popular Types of Loss Functions.mp4 |
86.75Мб |
| 001 Python Basics - Assignment.mp4 |
63.43Мб |
| 001 Redwine Quality MultiClass Classification Model - Introduction.mp4 |
37.11Мб |
| 001 ResNet50 Prediction.mp4 |
94.23Мб |
| 001 Serialize and Save Trained Model for Later Use.mp4 |
49.14Мб |
| 001 Setting up Computer - Installing Anaconda.mp4 |
85.57Мб |
| 001 SOURCE CODE AND FILES ATTACHED.html |
1.05Кб |
| 001 Step1 - Fetch and Load Data.mp4 |
46.01Мб |
| 001 Step 1 - Fetch and Load Data.mp4 |
85.89Мб |
| 001 Step 2 and 3 EDA and Data Preparation - Part 1.mp4 |
149.77Мб |
| 001 Step 2 and 3 - EDA and Data Preparation - Part 1.mp4 |
69.10Мб |
| 001 Step 2 - EDA and Data Visualization.mp4 |
101.08Мб |
| 001 Step 3 - Defining the Model.mp4 |
72.82Мб |
| 001 Step 4 - Compile Fit and Plot the Model.mp4 |
78.17Мб |
| 001 Step 4 Defining the Keras Model - Part 1.mp4 |
58.17Мб |
| 001 Step 4 - Defining the model.mp4 |
65.42Мб |
| 001 Step 5 and 6 Compile and Fit Model.mp4 |
110.25Мб |
| 001 Step 5 - Compile Fit and Plot the Model.mp4 |
74.42Мб |
| 001 Step 5 - Predicting Heart Disease using Model.mp4 |
50.06Мб |
| 001 Step 5 - Predicting Wine Quality using Model.mp4 |
42.02Мб |
| 001 Step 7 Visualize Training and Metrics.mp4 |
83.53Мб |
| 001 Step 8 Prediction Using the Model.mp4 |
48.13Мб |
| 001 Stride Padding and Flattening Concepts of CNN.mp4 |
96.13Мб |
| 001 Transfer Learning using Pretrained Models - VGG Introduction.mp4 |
95.91Мб |
| 001 VGG16 and VGG19 prediction - Part 1.mp4 |
100.73Мб |
| 001 VGG16 Transfer Learning Flower Prediction.mp4 |
27.48Мб |
| 001 VGG16 Transfer Learning Training Flowers Dataset - part 1.mp4 |
76.67Мб |
| 002 Basic Image Processing using Keras Functions - Part 2.mp4 |
65.45Мб |
| 002 Flowers Classification CNN - Defining the Model - Part 2.mp4 |
89.03Мб |
| 002 Hyper Parameter Tuning - Part 2.mp4 |
125.61Мб |
| 002 Keras Single Image Augmentation - Part 2.mp4 |
95.03Мб |
| 002 Matplotlib Basics - part 2.mp4 |
37.99Мб |
| 002 Numpy Basics - Part 2.mp4 |
52.78Мб |
| 002 Pandas Basics - Part 2.mp4 |
33.57Мб |
| 002 Python Basics - Flow Control - Part 1.mp4 |
46.83Мб |
| 002 Step 2 and 3 EDA and Data Preparation - Part 2.mp4 |
120.41Мб |
| 002 Step 2 and 3 - EDA and Data Preparation - Part 2.mp4 |
76.19Мб |
| 002 Step 4 Defining the Keras Model - Part 2.mp4 |
64.54Мб |
| 002 VGG16 and VGG19 prediction - Part 2.mp4 |
46.51Мб |
| 002 VGG16 Transfer Learning Training Flowers Dataset - part 2.mp4 |
106.31Мб |
| 003 Basic Image Processing using Keras Functions - Part 3.mp4 |
46.44Мб |
| 003 Flowers Classification CNN - Defining the Model - Part 3.mp4 |
36.79Мб |
| 003 Python Basics - Flow Control - Part 2.mp4 |
36.43Мб |
| 004 Python Basics - List and Tuples.mp4 |
46.08Мб |
| 005 Python Basics - Dictionary and Functions - part 1.mp4 |
53.60Мб |
| 006 Python Basics - Dictionary and Functions - part 2.mp4 |
33.93Мб |
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| TutsNode.com.txt |
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