Data Science - CNN and OpenCV - Breast Cancer Detection --> [ DevCourseWeb ]
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Data Science - CNN and OpenCV - Breast Cancer Detection --> [ DevCourseWeb ]
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Torrent File Content (64 files)
[ DevCourseWeb.com ] Udemy - Data Science - CNN and OpenCV - Breast Cancer Detection
Get Bonus Downloads Here.url -
Get Bonus Downloads Here.url -
182 bytes
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1. Introduction and Getting Started/1. Project Overview.mp4 -
1. Introduction and Getting Started/1. Project Overview.mp4 -
6.74 MB
1. Introduction and Getting Started/2. Introduction to Google Colab.mp4 -
15.53 MB
1. Introduction and Getting Started/3. Understanding the project folder structure.mp4 -
26.86 MB
10. Fitting the Model/1. About Epoch and Batch Size.mp4 -
5.67 MB
10. Fitting the Model/2. Model Fitting of ResNet50, Custom CNN.mp4 -
40.85 MB
11. Model Evaluation/1. Predicting on the test data using ResNet50 and Custom CNN Model.mp4 -
29.18 MB
11. Model Evaluation/2. About Classification Report.mp4 -
7.1 MB
11. Model Evaluation/3. Classification Report in action for ResNet50 and Custom CNN Model.mp4 -
15.67 MB
11. Model Evaluation/4. About Confusion Matrix.mp4 -
9.54 MB
11. Model Evaluation/5. Computing the confusion matrix and using the same to derive the accuracy, sensit.mp4 -
19.31 MB
11. Model Evaluation/6. About AUC-ROC.mp4 -
5.73 MB
11. Model Evaluation/7. Computing the AUC-ROC.mp4 -
6.19 MB
11. Model Evaluation/8. Plot training and validation accuracy and loss.mp4 -
8.83 MB
11. Model Evaluation/9. SerializeWriting the model to disk.mp4 -
17 MB
12. Using ResNet50 model to detect presence of malignant cells in images/1. Loading the ResNet50 model from drive.mp4 -
27.54 MB
12. Using ResNet50 model to detect presence of malignant cells in images/2. Loading an image and predicting using the model whether the person has malignant.mp4 -
45.66 MB
13. Using custom CNN model to detect presence of malignant cells in images/1. Loading the custom CNN model from drive.mp4 -
16.69 MB
13. Using custom CNN model to detect presence of malignant cells in images/2. Loading an image and predicting using the model whether the person has malignant.mp4 -
28.71 MB
14. Future scope of work/1. What you can do next to increase model’s prediction capabilities..mp4 -
25.16 MB
15. Project Files and Code/1. Full Project Code.html -
78 bytes
15. Project Files and Code/Detect_BreastCancer.ipynb -
16.11 KB
15. Project Files and Code/Kaggle Link.txt -
78 bytes
15. Project Files and Code/output/CM_TrainingHistoryPlot.png -
25.78 KB
15. Project Files and Code/output/CM_weights-010-0.3063.hdf5 -
42.31 MB
15. Project Files and Code/output/RN_TrainingHistoryPlot.png -
23.82 KB
15. Project Files and Code/output/RN_weights-009-0.3958.hdf5 -
96.5 MB
15. Project Files and Code/sampleTest_Pictures/benign.png -
5.86 KB
15. Project Files and Code/sampleTest_Pictures/malignant.png -
6.55 KB
15. Project Files and Code/train_CustomModel_32_conv_20k.ipynb -
787.63 KB
15. Project Files and Code/train_ResNet50_32_20k.ipynb -
843.09 KB
15. Project Files and Code/utils/config.py -
1.14 KB
15. Project Files and Code/utils/conv_bc_model.py -
3.38 KB
15. Project Files and Code/utils/create_dataset.py -
1.88 KB
15. Project Files and Code/utils/getPaths.py -
1.01 KB
2. Data Understanding & Importing Libraries/1. Understanding the dataset and the folder structure.mp4 -
26.79 MB
2. Data Understanding & Importing Libraries/2. Setting up the project in Google Colab_Part 1.mp4 -
6.36 MB
2. Data Understanding & Importing Libraries/3. Setting up the project in Google Colab_Part 2.mp4 -
82.95 MB
2. Data Understanding & Importing Libraries/4. About Config and Create_Dataset File.mp4 -
82.88 MB
2. Data Understanding & Importing Libraries/5. Importing the Libraries.mp4 -
33.53 MB
2. Data Understanding & Importing Libraries/6. Plotting the count of data against each class in each directory.mp4 -
27.71 MB
2. Data Understanding & Importing Libraries/7. Plotting some samples from both the classes.mp4 -
34.84 MB
3. Common Methods for plotting and class weight calculation/1. Creating a common method to get the number of files from a directory.mp4 -
7.69 MB
3. Common Methods for plotting and class weight calculation/2. Defining a method to plot training and validation accuracy and loss.mp4 -
17.29 MB
3. Common Methods for plotting and class weight calculation/3. Calculating the class weights in train directory.mp4 -
31.91 MB
4. Data Augmentation/1. About Data Augmentation.mp4 -
18.14 MB
4. Data Augmentation/2. Implementing Data Augmentation techniques.mp4 -
30.27 MB
5. Data Generators/1. About Data Generators.mp4 -
15.05 MB
5. Data Generators/2. Implementing Data Generators.mp4 -
26.92 MB
6. About CNN and Pre-trained Models/1. About Convolutional Neural Network (CNN).mp4 -
12.53 MB
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