Data Science: CNN & OpenCV: Breast Cancer Detection
https://DevCourseWeb.com
Published 12/2022 Created by AutomationGig . MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 48 Lectures ( 2h 13m ) | Size: 1.13 GB
A practical hands on Deep Learning Project on building a Breast Cancer Detection model using Tensorflow, CNN and OpenCV
What you'll learn Data Analysis and Understanding Data Augumentation Data Generators Model Checkpoints CNN and OpenCV Pretrained Models like ResNet50 Compiling and Fitting a customized pretrained model Model Evaluation Model Serialization Classification Metrics Model Evaluation Using trained model to detect Pneumonia using Chest XRays
Requirements Basics knowledge of Python, Neural Networks and OpenCV is recommended
~Get Your Files Here !/1. Introduction and Getting Started/1. Project Overview.mp4
6.7 MB
~Get Your Files Here !/1. Introduction and Getting Started/2. Introduction to Google Colab.mp4
15.5 MB
~Get Your Files Here !/1. Introduction and Getting Started/3. Understanding the project folder structure.mp4
26.9 MB
~Get Your Files Here !/10. Fitting the Model/1. About Epoch and Batch Size.mp4
5.7 MB
~Get Your Files Here !/10. Fitting the Model/2. Model Fitting of ResNet50, Custom CNN.mp4
40.9 MB
~Get Your Files Here !/11. Model Evaluation/1. Predicting on the test data using ResNet50 and Custom CNN Model.mp4
29.2 MB
~Get Your Files Here !/11. Model Evaluation/2. About Classification Report.mp4
7.1 MB
~Get Your Files Here !/11. Model Evaluation/3. Classification Report in action for ResNet50 and Custom CNN Model.mp4
15.7 MB
~Get Your Files Here !/11. Model Evaluation/4. About Confusion Matrix.mp4
9.5 MB
~Get Your Files Here !/11. Model Evaluation/5. Computing the confusion matrix and using the same to derive the accuracy, sensit.mp4
19.3 MB
~Get Your Files Here !/11. Model Evaluation/6. About AUC-ROC.mp4
5.7 MB
~Get Your Files Here !/11. Model Evaluation/7. Computing the AUC-ROC.mp4
6.2 MB
~Get Your Files Here !/11. Model Evaluation/8. Plot training and validation accuracy and loss.mp4
8.8 MB
~Get Your Files Here !/11. Model Evaluation/9. SerializeWriting the model to disk.mp4
17 MB
~Get Your Files Here !/12. Using ResNet50 model to detect presence of malignant cells in images/1. Loading the ResNet50 model from drive.mp4
27.5 MB
~Get Your Files Here !/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
45.7 MB
~Get Your Files Here !/13. Using custom CNN model to detect presence of malignant cells in images/1. Loading the custom CNN model from drive.mp4
16.7 MB
~Get Your Files Here !/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
28.7 MB
~Get Your Files Here !/14. Future scope of work/1. What you can do next to increase model’s prediction capabilities..mp4
25.2 MB
~Get Your Files Here !/15. Project Files and Code/1. Full Project Code.html
78 B
~Get Your Files Here !/15. Project Files and Code/Detect_BreastCancer.ipynb
16.1 KB
~Get Your Files Here !/15. Project Files and Code/Kaggle Link.txt
78 B
~Get Your Files Here !/15. Project Files and Code/output/CM_TrainingHistoryPlot.png
25.8 KB
~Get Your Files Here !/15. Project Files and Code/output/CM_weights-010-0.3063.hdf5
42.3 MB
~Get Your Files Here !/15. Project Files and Code/output/RN_TrainingHistoryPlot.png
23.8 KB
~Get Your Files Here !/15. Project Files and Code/output/RN_weights-009-0.3958.hdf5
96.5 MB
~Get Your Files Here !/15. Project Files and Code/sampleTest_Pictures/benign.png
5.9 KB
~Get Your Files Here !/15. Project Files and Code/sampleTest_Pictures/malignant.png
6.6 KB
~Get Your Files Here !/15. Project Files and Code/train_CustomModel_32_conv_20k.ipynb
787.6 KB
~Get Your Files Here !/15. Project Files and Code/train_ResNet50_32_20k.ipynb
843.1 KB
~Get Your Files Here !/15. Project Files and Code/utils/config.py
1.1 KB
~Get Your Files Here !/15. Project Files and Code/utils/conv_bc_model.py
3.4 KB
~Get Your Files Here !/15. Project Files and Code/utils/create_dataset.py
1.9 KB
~Get Your Files Here !/15. Project Files and Code/utils/getPaths.py
1 KB
~Get Your Files Here !/2. Data Understanding & Importing Libraries/1. Understanding the dataset and the folder structure.mp4
26.8 MB
~Get Your Files Here !/2. Data Understanding & Importing Libraries/2. Setting up the project in Google Colab_Part 1.mp4
6.4 MB
~Get Your Files Here !/2. Data Understanding & Importing Libraries/3. Setting up the project in Google Colab_Part 2.mp4
82.9 MB
~Get Your Files Here !/2. Data Understanding & Importing Libraries/4. About Config and Create_Dataset File.mp4
82.9 MB
~Get Your Files Here !/2. Data Understanding & Importing Libraries/5. Importing the Libraries.mp4
33.5 MB
~Get Your Files Here !/2. Data Understanding & Importing Libraries/6. Plotting the count of data against each class in each directory.mp4
27.7 MB
~Get Your Files Here !/2. Data Understanding & Importing Libraries/7. Plotting some samples from both the classes.mp4
34.8 MB
~Get Your Files Here !/3. Common Methods for plotting and class weight calculation/1. Creating a common method to get the number of files from a directory.mp4
7.7 MB
~Get Your Files Here !/3. Common Methods for plotting and class weight calculation/2. Defining a method to plot training and validation accuracy and loss.mp4
17.3 MB
~Get Your Files Here !/3. Common Methods for plotting and class weight calculation/3. Calculating the class weights in train directory.mp4
31.9 MB
~Get Your Files Here !/4. Data Augmentation/1. About Data Augmentation.mp4
18.1 MB
~Get Your Files Here !/4. Data Augmentation/2. Implementing Data Augmentation techniques.mp4
30.3 MB
~Get Your Files Here !/5. Data Generators/1. About Data Generators.mp4
15 MB
~Get Your Files Here !/5. Data Generators/2. Implementing Data Generators.mp4
26.9 MB
~Get Your Files Here !/6. About CNN and Pre-trained Models/1. About Convolutional Neural Network (CNN).mp4
12.5 MB
~Get Your Files Here !/6. About CNN and Pre-trained Models/2. About OpenCV.mp4
16.6 MB
~Get Your Files Here !/6. About CNN and Pre-trained Models/3. Understanding pre-trained models.mp4
10.8 MB
~Get Your Files Here !/6. About CNN and Pre-trained Models/4. About ResNet50 model.mp4
8 MB
~Get Your Files Here !/6. About CNN and Pre-trained Models/5. Understanding Conv2D, Filters, Relu activation, Batch Normalization, MaxPooling2.mp4
22.8 MB
~Get Your Files Here !/7. Model Building/1. Model Building using ResNet50.mp4
38.7 MB
~Get Your Files Here !/7. Model Building/2. Building a custom CNN network architecture.mp4
52.1 MB
~Get Your Files Here !/8. Compiling the Model/1. Role of Optimizer in Deep Learning.mp4
17.5 MB
~Get Your Files Here !/8. Compiling the Model/2. About Adam Optimizer.mp4
5.2 MB
~Get Your Files Here !/8. Compiling the Model/3. About binary cross entropy loss function..mp4
11.7 MB
~Get Your Files Here !/8. Compiling the Model/4. Compiling the ResNet50 model.mp4
8.9 MB
~Get Your Files Here !/8. Compiling the Model/5. Compiling the Custom CNN Model.mp4
4.8 MB
~Get Your Files Here !/9. ModelCheckpoint/1. About Model Checkpoint.mp4
6.2 MB
~Get Your Files Here !/9. ModelCheckpoint/2. Implementing Model Checkpoint.mp4
23.2 MB
~Get Your Files Here !/Bonus Resources.txt
386 B
Alternative Torrents for 'Udemy Data Science CNN and OpenCV Breast Cancer Detection'.
