Download Udemy - Data Science - CNN and OpenCV - Chest XRAY-Pneumonia Detection Torrent

Torrent Contents Size: 1.1 GB

Udemy - Data Science - CNN and OpenCV - Chest XRAY-Pneumonia Detection

▼ show more 87 files

1. About Convolutional Neural Network (CNN).mp4	MP4	12 MB
1. About Convolutional Neural Network (CNN).srt	SRT	2.5 KB
1. About Data Augmentation.mp4	MP4	17.1 MB
1. About Data Augmentation.srt	SRT	3.3 KB
1. About Data Generators.mp4	MP4	14.5 MB
1. About Data Generators.srt	SRT	3.2 KB
1. About Epoch and Batch Size.mp4	MP4	5.4 MB
1. About Epoch and Batch Size.srt	SRT	1.4 KB
1. About Model Checkpoint.mp4	MP4	5.9 MB
1. About Model Checkpoint.srt	SRT	1.5 KB
1. Creating a common method to get the number of files from a directory.mp4	MP4	8.5 MB
1. Creating a common method to get the number of files from a directory.srt	SRT	1.5 KB
1. Full Project Code.html	HTML	102.4 B
1. Loading the final model from drive.mp4	MP4	19.8 MB
1. Loading the final model from drive.srt	SRT	3.6 KB
1. Predicting on the test data using both MobileNetV2 and Custom CNN Model.mp4	MP4	22.3 MB
1. Predicting on the test data using both MobileNetV2 and Custom CNN Model.srt	SRT	4.5 KB
1. Project Overview.mp4	MP4	5.7 MB
1. Project Overview.srt	SRT	1.6 KB
1. Role of Optimizer in Deep Learning.mp4	MP4	16.5 MB
1. Role of Optimizer in Deep Learning.srt	SRT	3.2 KB
1. Understanding the dataset and the folder structure.mp4	MP4	17 MB
1. Understanding the dataset and the folder structure.srt	SRT	5.6 KB
2. About Adam Optimizer.mp4	MP4	5 MB
2. About Adam Optimizer.srt	SRT	1.5 KB
2. About Classification Report.mp4	MP4	7 MB
2. About Classification Report.srt	SRT	1.6 KB
2. About OpenCV.mp4	MP4	17.9 MB
2. About OpenCV.srt	SRT	2.8 KB
2. Defining a method to plot training and validation accuracy and loss.mp4	MP4	25.9 MB
2. Defining a method to plot training and validation accuracy and loss.srt	SRT	4.7 KB
2. Implementing Data Augmentation techniques.mp4	MP4	24.6 MB
2. Implementing Data Augmentation techniques.srt	SRT	4.3 KB
2. Implementing Data Generators.mp4	MP4	23.4 MB
2. Implementing Data Generators.srt	SRT	4.3 KB
2. Implementing Model Checkpoint.mp4	MP4	21.9 MB
2. Implementing Model Checkpoint.srt	SRT	4 KB
2. Introduction to Google Colab.mp4	MP4	15.2 MB
2. Introduction to Google Colab.srt	SRT	3.5 KB
2. Loading an image and predicting using the model whether the person has Pneumonia.mp4	MP4	40.1 MB
2. Loading an image and predicting using the model whether the person has Pneumonia.srt	SRT	6.3 KB
2. MobileNetV2 and Custom CNN Model Fitting.mp4	MP4	42.6 MB
2. MobileNetV2 and Custom CNN Model Fitting.srt	SRT	6 KB
2. Setting up the project in Google Colab_Part1.mp4	MP4	6.1 MB
2. Setting up the project in Google Colab_Part1.srt	SRT	1.5 KB
3. About binary cross entropy loss function..mp4	MP4	11.2 MB
3. About binary cross entropy loss function..srt	SRT	2.4 KB
3. Calculating the class weights in train directory.mp4	MP4	35.2 MB
3. Calculating the class weights in train directory.srt	SRT	6.3 KB
3. Classification Report in action for both MobileNetV2 and Custom CNN Model.mp4	MP4	14.5 MB
3. Classification Report in action for both MobileNetV2 and Custom CNN Model.srt	SRT	2.7 KB
3. Setting up the project in Google Colab_Part2.mp4	MP4	80.6 MB
3. Setting up the project in Google Colab_Part2.srt	SRT	16 KB
3. Understanding pre-trained models.mp4	MP4	10 MB
3. Understanding pre-trained models.srt	SRT	2.1 KB
3. Understanding the project folder structure.mp4	MP4	15.4 MB
3. Understanding the project folder structure.srt	SRT	4.8 KB
4. About Config and Create_Dataset File.mp4	MP4	72.4 MB
4. About Config and Create_Dataset File.srt	SRT	14.3 KB
4. About MobileNetV2 model.mp4	MP4	7.6 MB
4. About MobileNetV2 model.srt	SRT	1.7 KB
4. Computing the confusion matrix and using the same to derive the accuracy, sensit.mp4	MP4	38.3 MB
4. Computing the confusion matrix and using the same to derive the accuracy, sensit.srt	SRT	7.6 KB
4. Putting all together for MobileNetV2.mp4	MP4	10.9 MB
4. Putting all together for MobileNetV2.srt	SRT	2.1 KB
5. Importing the Libraries.mp4	MP4	37.2 MB
5. Importing the Libraries.srt	SRT	6 KB
5. Loading the MobileNetV2 classifier.mp4	MP4	16.4 MB
5. Loading the MobileNetV2 classifier.srt	SRT	1.7 KB
5. Plot training and validation accuracy and loss.mp4	MP4	14.9 MB
5. Plot training and validation accuracy and loss.srt	SRT	2.9 KB
5. Putting all together for Custom CNN Model.mp4	MP4	12.3 MB
5. Putting all together for Custom CNN Model.srt	SRT	2.3 KB
6. Building a new fully-connected (FC) head.mp4	MP4	20.3 MB
6. Building a new fully-connected (FC) head.srt	SRT	2.9 KB
6. Plotting the count of data against each class in each directory.mp4	MP4	51 MB
6. Plotting the count of data against each class in each directory.srt	SRT	10.3 KB
6. SerializeWriting the model to disk.mp4	MP4	7.1 MB
6. SerializeWriting the model to disk.srt	SRT	1.5 KB
7. Building the final MobileNetV2 model.mp4	MP4	8.9 MB
7. Building the final MobileNetV2 model.srt	SRT	1.7 KB
7. Plotting some samples from both the classes.mp4	MP4	46.8 MB
7. Plotting some samples from both the classes.srt	SRT	7.8 KB
8. Understanding Conv2D, Filters, Relu activation, Batch Normalization, MaxPooling2.mp4	MP4	26.8 MB
8. Understanding Conv2D, Filters, Relu activation, Batch Normalization, MaxPooling2.srt	SRT	3.7 KB
9. Building a custom CNN network architecture.mp4	MP4	76.1 MB
9. Building a custom CNN network architecture.srt	SRT	13.3 KB
Bonus Resources.txt	TXT	409.6 B
CM_16_weights-018-0.1818.hdf5	HDF5	89.4 MB
Detect_Pneumonia.ipynb	IPYNB	697.6 KB
Get Bonus Downloads Here.url	URL	204.8 B
Kaggle Link_chest-xray-pneumonia.txt	TXT	102.4 B
MN_16_TrainingHistoryPlot.png	PNG	24.7 KB
MN_16_weights-016-0.2087.hdf5	HDF5	11 MB
Normal.jpeg	JPEG	246.8 KB
Pneumonia.jpeg	JPEG	75.6 KB
config.py	PY	1.1 KB
conv_bc_model.py	PY	2.7 KB
create_dataset.py	PY	1.8 KB
getPaths.py	PY	1 KB
train_CustomModel_16_conv_modelCheckpoint_reshuffle_data.ipynb	IPYNB	857.8 KB
train_MobileNet_16_modelCheckpoint_reshuffle_data (1).ipynb	IPYNB	891.7 KB

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Udemy - Data Science - CNN and OpenCV - Chest XRAY-Pneumonia Detection

Torrent Contents Size: 1.1 GB

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