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| [TGx]Downloaded from torrentgalaxy.to .txt |
585б |
| 0 |
92б |
| 1 |
35б |
| 1. Deep Learning Overview.mp4 |
96.82Мб |
| 1. Deep Learning Overview.srt |
16.24Кб |
| 1. Image Fundamentals.mp4 |
90.06Мб |
| 1. Image Fundamentals.srt |
10.37Кб |
| 1. Introduction.mp4 |
22.59Мб |
| 1. Introduction.mp4 |
6.35Мб |
| 1. Introduction.srt |
1.56Кб |
| 1. Introduction.srt |
1.05Кб |
| 1. Introduction to the course.mp4 |
40.31Мб |
| 1. Introduction to the course.srt |
3.34Кб |
| 10 |
594.43Кб |
| 10.1 Yolo v1.html |
97б |
| 10.2 YOLOv1.pdf |
5.05Мб |
| 10.3 YOLOv2.pdf |
5.02Мб |
| 10. Fully Connected Layer.mp4 |
44.59Мб |
| 10. Fully Connected Layer.srt |
6.18Кб |
| 10. The YOLO (You only look once) Model.mp4 |
161.09Мб |
| 10. The YOLO (You only look once) Model.srt |
23.22Кб |
| 11 |
72.62Кб |
| 11.1 YOLOv2.pdf |
5.02Мб |
| 11. Load data from image directory in TensorFlow 2.mp4 |
74.15Мб |
| 11. Load data from image directory in TensorFlow 2.srt |
15.90Кб |
| 11. YOLOv2 the first upgrade of the model.mp4 |
127.39Мб |
| 11. YOLOv2 the first upgrade of the model.srt |
19.23Кб |
| 12 |
149.51Кб |
| 12.1 Yolo repo.html |
96б |
| 12.2 Yolo v2 web page.html |
97б |
| 12.3 yolo_installation.txt |
528б |
| 12.4 yolo.zip |
180.51Мб |
| 12. Create a ConvNet - CIFAR10 - Tensorflow 2 - Part 1.mp4 |
80.23Мб |
| 12. Running YOLO v2 on images.mp4 |
159.85Мб |
| 12. Running YOLO v2 on images.srt |
18.49Кб |
| 13 |
81.40Кб |
| 13.1 Yolo v2 web page.html |
97б |
| 13. Create a ConvNet - CIFAR10 - Tensorflow 2.mp4 |
100.48Мб |
| 13. YOLOv2 on video and webcam.mp4 |
142.90Мб |
| 13. YOLOv2 on video and webcam.srt |
13.98Кб |
| 14 |
344.07Кб |
| 14.1 rd2d2.zip |
40.69Мб |
| 14.2 Yolo v2 web page.html |
97б |
| 14.3 Yolo v3 web page.html |
95б |
| 14.4 yolov2_weights.zip |
180.51Мб |
| 14.5 yolov2-1c.zip |
741б |
| 14. Data Augmentation with TF2.X - Keras.mp4 |
94.56Мб |
| 14. Data Augmentation with TF2.X - Keras.srt |
18.28Кб |
| 14. Detecting custom objects with Yolo v2.mp4 |
108.30Мб |
| 14. Detecting custom objects with Yolo v2.srt |
13.63Кб |
| 15 |
137.88Кб |
| 15.1 covid19.zip |
157.29Мб |
| 15.1 Yolov2-training your own dataset in Jupyter.zip |
725.96Кб |
| 15. Detect COVID19 on X-Ray images.mp4 |
103.67Мб |
| 15. Detect COVID19 on X-Ray images.srt |
19.34Кб |
| 15. Detecting custom objects with Yolov2 in Jupyter.mp4 |
118.25Мб |
| 15. Detecting custom objects with Yolov2 in Jupyter.srt |
21.16Кб |
| 16 |
104.15Кб |
| 16.1 cudnn-10.0-linux-x64-v7.5.0.56.tgz |
412.76Мб |
| 16.2 darknet53.conv.74.zip |
144.14Мб |
| 16.3 yolov3_custom_dataset.zip |
778.20Кб |
| 16.4 YOLOv3.pdf |
2.29Мб |
| 16. Pretrained Models - VGG16.mp4 |
64.14Мб |
| 16. Pretrained Models - VGG16.srt |
9.25Кб |
| 16. Train your own dataset in Yolov3-Colab-Part 1.mp4 |
138.65Мб |
| 16. Train your own dataset in Yolov3-Colab-Part 1.srt |
20.87Кб |
| 17 |
361.44Кб |
| 17.1 Deep_Residual_Networks(ResNet).pdf |
800.18Кб |
| 17.2 DenseNet.pdf |
1.09Мб |
| 17.3 ResNeXt.pdf |
1.27Мб |
| 17. ResNet Model.mp4 |
132.75Мб |
| 17. ResNet Model.srt |
23.00Кб |
| 17. Train your own dataset in Yolov3-Colab-Part 2.mp4 |
121.14Мб |
| 17. Train your own dataset in Yolov3-Colab-Part 2.srt |
15.30Кб |
| 18 |
260.47Кб |
| 18.1 ResNet50 Keras-Cifar10.zip |
1.86Кб |
| 18.1 Yolov4-Optimal Speed and Accuracy of Object Detection.pdf |
3.76Мб |
| 18. ResNet50 in Keras.mp4 |
126.91Мб |
| 18. ResNet50 in Keras.srt |
19.67Кб |
| 18. Yolov4 under the hood - Part 1.mp4 |
73.67Мб |
| 18. Yolov4 under the hood - Part 1.srt |
11.57Кб |
| 19 |
808.59Кб |
| 19.1 Going deeper with convolutions-Inception.pdf |
1.16Мб |
| 19. Inception Network.mp4 |
87.86Мб |
| 19. Inception Network.srt |
15.88Кб |
| 19. Yolov4 under the hood - Part 2.mp4 |
92.07Мб |
| 19. Yolov4 under the hood - Part 2.srt |
16.85Кб |
| 2 |
322.78Кб |
| 2.1 Image Web Scraping Selenium.zip |
2.91Кб |
| 2.1 selectiveSearch.pdf |
5.66Мб |
| 2. Convolutional Neural Network model.mp4 |
74.11Мб |
| 2. Convolutional Neural Network model.srt |
9.90Кб |
| 2. Google Colaboratory.mp4 |
32.81Мб |
| 2. Google Colaboratory.srt |
6.28Кб |
| 2. Gradient Descent.mp4 |
43.79Мб |
| 2. Gradient Descent.srt |
8.08Кб |
| 2. Scraping images with Selenium.mp4 |
160.42Мб |
| 2. Scraping images with Selenium.srt |
23.12Кб |
| 2. The beginnings Selective Search Algorithm.mp4 |
63.13Мб |
| 2. The beginnings Selective Search Algorithm.srt |
8.39Кб |
| 20 |
259.71Кб |
| 20.1 Cifar10-Inception-TF1.X.ipynb.zip |
33.25Кб |
| 20.1 yolov4_custom_dataset.zip |
809.53Кб |
| 20.2 yolov4.conv.137.zip |
150.66Мб |
| 20.3 yolov4.zip |
228.47Мб |
| 20. Inception Module with TensorFlow.mp4 |
135.21Мб |
| 20. Inception Module with TensorFlow.srt |
22.48Кб |
| 20. Train your custom dataset with Yolov4 in Google Colab.mp4 |
181.29Мб |
| 20. Train your custom dataset with Yolov4 in Google Colab.srt |
23.21Кб |
| 21 |
626.82Кб |
| 21. Final Class and Beyond.mp4 |
27.13Мб |
| 21. Final Class and Beyond.srt |
1.60Кб |
| 22 |
93.63Кб |
| 23 |
882.61Кб |
| 24 |
763.81Кб |
| 25 |
48.20Кб |
| 26 |
474.76Кб |
| 27 |
716.89Кб |
| 28 |
271.63Кб |
| 29 |
336.45Кб |
| 3 |
39б |
| 3.1 FiftyOne_OpenImagesV6.zip |
3.34Мб |
| 3.1 gradient descent optimization algorithms.pdf |
643.58Кб |
| 3. Beyond Gradient Descent.mp4 |
104.73Мб |
| 3. Beyond Gradient Descent.srt |
12.02Кб |
| 3. Convolutional Operation.mp4 |
116.95Мб |
| 3. Convolutional Operation.srt |
14.73Кб |
| 3. Install TensorFlow-GPU in local machine.mp4 |
115.54Мб |
| 3. Install TensorFlow-GPU in local machine.srt |
14.36Кб |
| 3. Metrics in Object Detection Models.mp4 |
84.57Мб |
| 3. Metrics in Object Detection Models.srt |
13.95Кб |
| 3. Open Images Dataset V6 and Voxel FiftyOne.mp4 |
166.91Мб |
| 3. Open Images Dataset V6 and Voxel FiftyOne.srt |
17.55Кб |
| 30 |
600.48Кб |
| 31 |
372.97Кб |
| 32 |
534.82Кб |
| 33 |
187.44Кб |
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374.56Кб |
| 35 |
445.47Кб |
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956.13Кб |
| 37 |
967.29Кб |
| 38 |
179.72Кб |
| 39 |
148.13Кб |
| 4 |
503.71Кб |
| 4.1 CV-TF1.X-2.X.zip |
498.13Мб |
| 4.1 Fast-R-CNN.pdf |
713.99Кб |
| 4.2 requirements.txt |
116б |
| 4. Codes and Resources.html |
148б |
| 4. Convolution Operation examples.mp4 |
39.96Мб |
| 4. Convolution Operation examples.srt |
6.02Кб |
| 4. Fast R-CNN.mp4 |
59.08Мб |
| 4. Fast R-CNN.srt |
8.33Кб |
| 4. Loss Functions.mp4 |
53.90Мб |
| 4. Loss Functions.srt |
8.70Кб |
| 4. Roboflow.mp4 |
136.75Мб |
| 4. Roboflow.srt |
17.36Кб |
| 40 |
91.87Кб |
| 41 |
486.08Кб |
| 42 |
440.83Кб |
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182.60Кб |
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1007.19Кб |
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867.05Кб |
| 47 |
912.04Кб |
| 48 |
339.95Кб |
| 49 |
357.71Кб |
| 5 |
503.72Кб |
| 5.1 Faster-r-cnn.pdf |
743.83Кб |
| 5. Conv2D Layer in Tensorflow 2-Keras.mp4 |
86.53Мб |
| 5. Faster R-CNN.mp4 |
75.02Мб |
| 5. Faster R-CNN.srt |
14.41Кб |
| 5. Labeling data with LabelImg.mp4 |
80.82Мб |
| 5. Labeling data with LabelImg.srt |
10.48Кб |
| 5. Regularization.mp4 |
70.65Мб |
| 5. Regularization.srt |
8.53Кб |
| 50 |
879.31Кб |
| 51 |
889.99Кб |
| 52 |
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98.01Кб |
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1012.04Кб |
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416.38Кб |
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213.39Кб |
| 57 |
320.67Кб |
| 58 |
705.89Кб |
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42.95Кб |
| 6 |
607.28Кб |
| 6.1 ssd.pdf |
2.20Мб |
| 6. Activation Functions.mp4 |
86.91Мб |
| 6. Activation Functions.srt |
13.48Кб |
| 6. Max Pooling.mp4 |
35.31Мб |
| 6. Max Pooling.srt |
7.69Кб |
| 6. SSD (Single Shot Detector).mp4 |
160.23Мб |
| 6. SSD (Single Shot Detector).srt |
21.73Кб |
| 60 |
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| 67 |
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| 68 |
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1001.11Кб |
| 7 |
415.32Кб |
| 7. Evaluating Activation Functions with Keras.mp4 |
88.82Мб |
| 7. Evaluating Activation Functions with Keras.srt |
13.78Кб |
| 7. ReLU function.mp4 |
50.01Мб |
| 7. ReLU function.srt |
5.47Кб |
| 7. TensorFlow2 Object Detection API on images and videos.mp4 |
168.59Мб |
| 7. TensorFlow2 Object Detection API on images and videos.srt |
22.53Кб |
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248.82Кб |
| 71 |
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| 8 |
96.56Кб |
| 8. Batch Normalization.mp4 |
95.63Мб |
| 8. Batch Normalization.srt |
8.11Кб |
| 8. Multilayer Perceptron with Keras.mp4 |
102.41Мб |
| 8. Multilayer Perceptron with Keras.srt |
13.85Кб |
| 8. Train Blood Cells Dataset in TensorFlow Object Detection part1.mp4 |
101.64Мб |
| 8. Train Blood Cells Dataset in TensorFlow Object Detection part1.srt |
13.23Кб |
| 9 |
156.54Кб |
| 9. DropOut.mp4 |
38.84Мб |
| 9. DropOut.srt |
4.27Кб |
| 9. Train Blood Cells Dataset in TensorFlow Object Detection part2.mp4 |
176.41Мб |
| 9. Train Blood Cells Dataset in TensorFlow Object Detection part2.srt |
20.50Кб |
| TutsNode.com.txt |
63б |