Deep Learning using Keras Complete Compact Dummies Guide | 3DFB50111B0EBC333101ED571E50191275C4050E

Deep Learning using Keras Complete Compact Dummies Guide

Name	Deep Learning using Keras - Complete & Compact Dummies Guide	DOWNLOAD Copy Link
Total Size	5.9 GB
Total Files	154
Last Seen	2024-10-04 23:54
Hash	3DFB50111B0EBC333101ED571E50191275C4050E

/.../01 Course Introduction and Table of Contents/
001 Course Introduction and Table of Contents.mp4	267.6 MB
/
TutsNode.com.txt	0.1 KB
[TGx]Downloaded from torrentgalaxy.to .txt	0.6 KB
/.../58 SOURCE CODE AND FILES ATTACHED/
001 SOURCE CODE AND FILES ATTACHED.html	1.1 KB
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/.../17 Step 2 and 3 EDA and Data Preparation/
001 Step 2 and 3 EDA and Data Preparation - Part 1.mp4	157.0 MB
002 Step 2 and 3 EDA and Data Preparation - Part 2.mp4	126.3 MB
/.../52 Hyper Parameter Tuning/
002 Hyper Parameter Tuning - Part 2.mp4	131.7 MB
001 Hyper Parameter Tuning - Part 1.mp4	102.7 MB
/.../40 CNN Basics/
001 CNN Basics.mp4	131.6 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
001 VGG16 Transfer Learning Training Flowers Dataset - part 1.mp4	80.4 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
002 Keras Single Image Augmentation - Part 2.mp4	99.7 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
002 VGG16 and VGG19 prediction - Part 2.mp4	48.8 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
/.../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
/.../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
001 Flowers Classification CNN - Defining the Model - Part 1.mp4	56.2 MB
003 Flowers Classification CNN - Defining the Model - Part 3.mp4	38.6 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
/.../24 Step 2 and 3 - EDA and Data Preparation/
002 Step 2 and 3 - EDA and Data Preparation - Part 2.mp4	79.9 MB
001 Step 2 and 3 - EDA and Data Preparation - Part 1.mp4	72.5 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
/.../36 Basic Image Processing using Keras Functions/
002 Basic Image Processing using Keras Functions - Part 2.mp4	68.6 MB
001 Basic Image Processing using Keras Functions - Part 1.mp4	65.7 MB
003 Basic Image Processing using Keras Functions - Part 3.mp4	48.7 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
001 Step 4 Defining the Keras Model - Part 1.mp4	61.0 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
005 Python Basics - Dictionary and Functions - part 1.mp4	56.2 MB
002 Python Basics - Flow Control - Part 1.mp4	49.1 MB
004 Python Basics - List and Tuples.mp4	48.3 MB
003 Python Basics - Flow Control - Part 2.mp4	38.2 MB
006 Python Basics - Dictionary and Functions - part 2.mp4	35.6 MB
/.../10 Basic Structure of Artificial Neuron and Neural Network/
001 Basic Structure of Artificial Neuron and Neural Network.mp4	66.1 MB
/.../08 Pandas Basics/
001 Pandas Basics - Part 1.mp4	61.4 MB
002 Pandas Basics - Part 2.mp4	35.2 MB
/.../51 Flowers Classification CNN - Augmentation Optimization/
001 Flowers Classification CNN - Augmentation Optimization.mp4	61.4 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
001 Numpy Basics - Part 1.mp4	43.0 MB
/.../07 Matplotlib Basics/
001 Matplotlib Basics - part 1.mp4	53.7 MB
002 Matplotlib Basics - part 2.mp4	39.8 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
/.../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
/.../48 Flowers Classification CNN - Optimization Techniques - Introduction/
001 Flowers Classification CNN - Optimization Techniques - Introduction.mp4	42.5 MB
/.../28 Redwine Quality MultiClass Classification Model - Introduction/
001 Redwine Quality MultiClass Classification Model - Introduction.mp4	38.9 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
Total files 154