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Deep Learning for Computer Vision with TensorFlow 2
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[TutsNode.com] - Deep Learning for Computer Vision with TensorFlow 2 (Size: 7.32 GB) (Files: 229)
[TutsNode.com] - Deep Learning for Computer Vision with TensorFlow 2
1. Installation and Setup
4.1 CV-TF1.X-2.X.zip
4. Codes and Resources.html
4.2 requirements.txt
3. Install TensorFlow-GPU in local machine.srt
2. Google Colaboratory.srt
1. Introduction to the course.srt
3. Install TensorFlow-GPU in local machine.mp4
1. Introduction to the course.mp4
2. Google Colaboratory.mp4
5. Object Detection
20.1 yolov4_custom_dataset.zip
10. The YOLO (You only look once) Model.srt
20. Train your custom dataset with Yolov4 in Google Colab.srt
10.1 Yolo v1.html
7. TensorFlow2 Object Detection API on images and videos.srt
6. SSD (Single Shot Detector).srt
15. Detecting custom objects with Yolov2 in Jupyter.srt
16. Train your own dataset in Yolov3-Colab-Part 1.srt
9. Train Blood Cells Dataset in TensorFlow Object Detection part2.srt
12.2 Yolo v2 web page.html
13.1 Yolo v2 web page.html
14.2 Yolo v2 web page.html
12.1 Yolo repo.html
16.1 cudnn-10.0-linux-x64-v7.5.0.56.tgz
11. YOLOv2 the first upgrade of the model.srt
12. Running YOLO v2 on images.srt
19. Yolov4 under the hood - Part 2.srt
17. Train your own dataset in Yolov3-Colab-Part 2.srt
5. Faster R-CNN.srt
13. YOLOv2 on video and webcam.srt
3. Metrics in Object Detection Models.srt
21. Final Class and Beyond.srt
20.3 yolov4.zip
14. Detecting custom objects with Yolo v2.srt
8. Train Blood Cells Dataset in TensorFlow Object Detection part1.srt
18. Yolov4 under the hood - Part 1.srt
2. The beginnings Selective Search Algorithm.srt
4. Fast R-CNN.srt
1. Introduction.srt
14.5 yolov2-1c.zip
12.3 yolo_installation.txt
14.3 Yolo v3 web page.html
20. Train your custom dataset with Yolov4 in Google Colab.mp4
15.1 Yolov2-training your own dataset in Jupyter.zip
14.4 yolov2_weights.zip
12.4 yolo.zip
9. Train Blood Cells Dataset in TensorFlow Object Detection part2.mp4
7. TensorFlow2 Object Detection API on images and videos.mp4
10. The YOLO (You only look once) Model.mp4
16.3 yolov3_custom_dataset.zip
6. SSD (Single Shot Detector).mp4
4.1 Fast-R-CNN.pdf
12. Running YOLO v2 on images.mp4
20.2 yolov4.conv.137.zip
16.2 darknet53.conv.74.zip
5.1 Faster-r-cnn.pdf
13. YOLOv2 on video and webcam.mp4
16. Train your own dataset in Yolov3-Colab-Part 1.mp4
11. YOLOv2 the first upgrade of the model.mp4
17. Train your own dataset in Yolov3-Colab-Part 2.mp4
15. Detecting custom objects with Yolov2 in Jupyter.mp4
14. Detecting custom objects with Yolo v2.mp4
8. Train Blood Cells Dataset in TensorFlow Object Detection part1.mp4
19. Yolov4 under the hood - Part 2.mp4
3. Metrics in Object Detection Models.mp4
5. Faster R-CNN.mp4
18. Yolov4 under the hood - Part 1.mp4
2. The beginnings Selective Search Algorithm.mp4
4. Fast R-CNN.mp4
14.1 rd2d2.zip
21. Final Class and Beyond.mp4
1. Introduction.mp4
2.1 selectiveSearch.pdf
10.2 YOLOv1.pdf
11.1 YOLOv2.pdf
10.3 YOLOv2.pdf
18.1 Yolov4-Optimal Speed and Accuracy of Object Detection.pdf
16.4 YOLOv3.pdf
6.1 ssd.pdf
3. Convolutional Neural Networks
20.1 Cifar10-Inception-TF1.X.ipynb.zip
17.1 Deep_Residual_Networks(ResNet).pdf
17. ResNet Model.srt
20. Inception Module with TensorFlow.srt
18. ResNet50 in Keras.srt
15. Detect COVID19 on X-Ray images.srt
14. Data Augmentation with TF2.X - Keras.srt
11. Load data from image directory in TensorFlow 2.srt
19. Inception Network.srt
3. Convolutional Operation.srt
1. Image Fundamentals.srt
2. Convolutional Neural Network model.srt
16. Pretrained Models - VGG16.srt
8. Batch Normalization.srt
6. Max Pooling.srt
10. Fully Connected Layer.srt
18.1 ResNet50 Keras-Cifar10.zip
4. Convolution Operation examples.srt
7. ReLU function.srt
9. DropOut.srt
15.1 covid19.zip
20. Inception Module with TensorFlow.mp4
17. ResNet Model.mp4
18. ResNet50 in Keras.mp4
3. Convolutional Operation.mp4
15. Detect COVID19 on X-Ray images.mp4
13. Create a ConvNet - CIFAR10 - Tensorflow 2.mp4
8. Batch Normalization.mp4
14. Data Augmentation with TF2.X - Keras.mp4
1. Image Fundamentals.mp4
19. Inception Network.mp4
5. Conv2D Layer in Tensorflow 2-Keras.mp4
12. Create a ConvNet - CIFAR10 - Tensorflow 2 - Part 1.mp4
11. Load data from image directory in TensorFlow 2.mp4
2. Convolutional Neural Network model.mp4
16. Pretrained Models - VGG16.mp4
7. ReLU function.mp4
10. Fully Connected Layer.mp4
4. Convolution Operation examples.mp4
9. DropOut.mp4
6. Max Pooling.mp4
17.3 ResNeXt.pdf
19.1 Going deeper with convolutions-Inception.pdf
17.2 DenseNet.pdf
4. Creating an Image Datasets
2. Scraping images with Selenium.srt
3. Open Images Dataset V6 and Voxel FiftyOne.srt
4. Roboflow.srt
5. Labeling data with LabelImg.srt
2.1 Image Web Scraping Selenium.zip
1. Introduction.srt
3. Open Images Dataset V6 and Voxel FiftyOne.mp4
2. Scraping images with Selenium.mp4
4. Roboflow.mp4
5. Labeling data with LabelImg.mp4
1. Introduction.mp4
3.1 FiftyOne_OpenImagesV6.zip
2. Deep Learning Overview
4. Loss Functions.srt
1. Deep Learning Overview.srt
8. Multilayer Perceptron with Keras.srt
7. Evaluating Activation Functions with Keras.srt
6. Activation Functions.srt
3. Beyond Gradient Descent.srt
5. Regularization.srt
2. Gradient Descent.srt
3.1 gradient descent optimization algorithms.pdf
3. Beyond Gradient Descent.mp4
8. Multilayer Perceptron with Keras.mp4
1. Deep Learning Overview.mp4
7. Evaluating Activation Functions with Keras.mp4
6. Activation Functions.mp4
5. Regularization.mp4
4. Loss Functions.mp4
2. Gradient Descent.mp4
TutsNode.com.txt
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