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| [TGx]Downloaded from torrentgalaxy.to .txt |
585B |
| 0 |
92B |
| 1 |
35B |
| 1. Deep Learning Overview.mp4 |
96.82MB |
| 1. Deep Learning Overview.srt |
16.24KB |
| 1. Image Fundamentals.mp4 |
90.06MB |
| 1. Image Fundamentals.srt |
10.37KB |
| 1. Introduction.mp4 |
22.59MB |
| 1. Introduction.mp4 |
6.35MB |
| 1. Introduction.srt |
1.56KB |
| 1. Introduction.srt |
1.05KB |
| 1. Introduction to the course.mp4 |
40.31MB |
| 1. Introduction to the course.srt |
3.34KB |
| 10 |
594.43KB |
| 10.1 Yolo v1.html |
97B |
| 10.2 YOLOv1.pdf |
5.05MB |
| 10.3 YOLOv2.pdf |
5.02MB |
| 10. Fully Connected Layer.mp4 |
44.59MB |
| 10. Fully Connected Layer.srt |
6.18KB |
| 10. The YOLO (You only look once) Model.mp4 |
161.09MB |
| 10. The YOLO (You only look once) Model.srt |
23.22KB |
| 11 |
72.62KB |
| 11.1 YOLOv2.pdf |
5.02MB |
| 11. Load data from image directory in TensorFlow 2.mp4 |
74.15MB |
| 11. Load data from image directory in TensorFlow 2.srt |
15.90KB |
| 11. YOLOv2 the first upgrade of the model.mp4 |
127.39MB |
| 11. YOLOv2 the first upgrade of the model.srt |
19.23KB |
| 12 |
149.51KB |
| 12.1 Yolo repo.html |
96B |
| 12.2 Yolo v2 web page.html |
97B |
| 12.3 yolo_installation.txt |
528B |
| 12.4 yolo.zip |
180.51MB |
| 12. Create a ConvNet - CIFAR10 - Tensorflow 2 - Part 1.mp4 |
80.23MB |
| 12. Running YOLO v2 on images.mp4 |
159.85MB |
| 12. Running YOLO v2 on images.srt |
18.49KB |
| 13 |
81.40KB |
| 13.1 Yolo v2 web page.html |
97B |
| 13. Create a ConvNet - CIFAR10 - Tensorflow 2.mp4 |
100.48MB |
| 13. YOLOv2 on video and webcam.mp4 |
142.90MB |
| 13. YOLOv2 on video and webcam.srt |
13.98KB |
| 14 |
344.07KB |
| 14.1 rd2d2.zip |
40.69MB |
| 14.2 Yolo v2 web page.html |
97B |
| 14.3 Yolo v3 web page.html |
95B |
| 14.4 yolov2_weights.zip |
180.51MB |
| 14.5 yolov2-1c.zip |
741B |
| 14. Data Augmentation with TF2.X - Keras.mp4 |
94.56MB |
| 14. Data Augmentation with TF2.X - Keras.srt |
18.28KB |
| 14. Detecting custom objects with Yolo v2.mp4 |
108.30MB |
| 14. Detecting custom objects with Yolo v2.srt |
13.63KB |
| 15 |
137.88KB |
| 15.1 covid19.zip |
157.29MB |
| 15.1 Yolov2-training your own dataset in Jupyter.zip |
725.96KB |
| 15. Detect COVID19 on X-Ray images.mp4 |
103.67MB |
| 15. Detect COVID19 on X-Ray images.srt |
19.34KB |
| 15. Detecting custom objects with Yolov2 in Jupyter.mp4 |
118.25MB |
| 15. Detecting custom objects with Yolov2 in Jupyter.srt |
21.16KB |
| 16 |
104.15KB |
| 16.1 cudnn-10.0-linux-x64-v7.5.0.56.tgz |
412.76MB |
| 16.2 darknet53.conv.74.zip |
144.14MB |
| 16.3 yolov3_custom_dataset.zip |
778.20KB |
| 16.4 YOLOv3.pdf |
2.29MB |
| 16. Pretrained Models - VGG16.mp4 |
64.14MB |
| 16. Pretrained Models - VGG16.srt |
9.25KB |
| 16. Train your own dataset in Yolov3-Colab-Part 1.mp4 |
138.65MB |
| 16. Train your own dataset in Yolov3-Colab-Part 1.srt |
20.87KB |
| 17 |
361.44KB |
| 17.1 Deep_Residual_Networks(ResNet).pdf |
800.18KB |
| 17.2 DenseNet.pdf |
1.09MB |
| 17.3 ResNeXt.pdf |
1.27MB |
| 17. ResNet Model.mp4 |
132.75MB |
| 17. ResNet Model.srt |
23.00KB |
| 17. Train your own dataset in Yolov3-Colab-Part 2.mp4 |
121.14MB |
| 17. Train your own dataset in Yolov3-Colab-Part 2.srt |
15.30KB |
| 18 |
260.47KB |
| 18.1 ResNet50 Keras-Cifar10.zip |
1.86KB |
| 18.1 Yolov4-Optimal Speed and Accuracy of Object Detection.pdf |
3.76MB |
| 18. ResNet50 in Keras.mp4 |
126.91MB |
| 18. ResNet50 in Keras.srt |
19.67KB |
| 18. Yolov4 under the hood - Part 1.mp4 |
73.67MB |
| 18. Yolov4 under the hood - Part 1.srt |
11.57KB |
| 19 |
808.59KB |
| 19.1 Going deeper with convolutions-Inception.pdf |
1.16MB |
| 19. Inception Network.mp4 |
87.86MB |
| 19. Inception Network.srt |
15.88KB |
| 19. Yolov4 under the hood - Part 2.mp4 |
92.07MB |
| 19. Yolov4 under the hood - Part 2.srt |
16.85KB |
| 2 |
322.78KB |
| 2.1 Image Web Scraping Selenium.zip |
2.91KB |
| 2.1 selectiveSearch.pdf |
5.66MB |
| 2. Convolutional Neural Network model.mp4 |
74.11MB |
| 2. Convolutional Neural Network model.srt |
9.90KB |
| 2. Google Colaboratory.mp4 |
32.81MB |
| 2. Google Colaboratory.srt |
6.28KB |
| 2. Gradient Descent.mp4 |
43.79MB |
| 2. Gradient Descent.srt |
8.08KB |
| 2. Scraping images with Selenium.mp4 |
160.42MB |
| 2. Scraping images with Selenium.srt |
23.12KB |
| 2. The beginnings Selective Search Algorithm.mp4 |
63.13MB |
| 2. The beginnings Selective Search Algorithm.srt |
8.39KB |
| 20 |
259.71KB |
| 20.1 Cifar10-Inception-TF1.X.ipynb.zip |
33.25KB |
| 20.1 yolov4_custom_dataset.zip |
809.53KB |
| 20.2 yolov4.conv.137.zip |
150.66MB |
| 20.3 yolov4.zip |
228.47MB |
| 20. Inception Module with TensorFlow.mp4 |
135.21MB |
| 20. Inception Module with TensorFlow.srt |
22.48KB |
| 20. Train your custom dataset with Yolov4 in Google Colab.mp4 |
181.29MB |
| 20. Train your custom dataset with Yolov4 in Google Colab.srt |
23.21KB |
| 21 |
626.82KB |
| 21. Final Class and Beyond.mp4 |
27.13MB |
| 21. Final Class and Beyond.srt |
1.60KB |
| 22 |
93.63KB |
| 23 |
882.61KB |
| 24 |
763.81KB |
| 25 |
48.20KB |
| 26 |
474.76KB |
| 27 |
716.89KB |
| 28 |
271.63KB |
| 29 |
336.45KB |
| 3 |
39B |
| 3.1 FiftyOne_OpenImagesV6.zip |
3.34MB |
| 3.1 gradient descent optimization algorithms.pdf |
643.58KB |
| 3. Beyond Gradient Descent.mp4 |
104.73MB |
| 3. Beyond Gradient Descent.srt |
12.02KB |
| 3. Convolutional Operation.mp4 |
116.95MB |
| 3. Convolutional Operation.srt |
14.73KB |
| 3. Install TensorFlow-GPU in local machine.mp4 |
115.54MB |
| 3. Install TensorFlow-GPU in local machine.srt |
14.36KB |
| 3. Metrics in Object Detection Models.mp4 |
84.57MB |
| 3. Metrics in Object Detection Models.srt |
13.95KB |
| 3. Open Images Dataset V6 and Voxel FiftyOne.mp4 |
166.91MB |
| 3. Open Images Dataset V6 and Voxel FiftyOne.srt |
17.55KB |
| 30 |
600.48KB |
| 31 |
372.97KB |
| 32 |
534.82KB |
| 33 |
187.44KB |
| 34 |
374.56KB |
| 35 |
445.47KB |
| 36 |
956.13KB |
| 37 |
967.29KB |
| 38 |
179.72KB |
| 39 |
148.13KB |
| 4 |
503.71KB |
| 4.1 CV-TF1.X-2.X.zip |
498.13MB |
| 4.1 Fast-R-CNN.pdf |
713.99KB |
| 4.2 requirements.txt |
116B |
| 4. Codes and Resources.html |
148B |
| 4. Convolution Operation examples.mp4 |
39.96MB |
| 4. Convolution Operation examples.srt |
6.02KB |
| 4. Fast R-CNN.mp4 |
59.08MB |
| 4. Fast R-CNN.srt |
8.33KB |
| 4. Loss Functions.mp4 |
53.90MB |
| 4. Loss Functions.srt |
8.70KB |
| 4. Roboflow.mp4 |
136.75MB |
| 4. Roboflow.srt |
17.36KB |
| 40 |
91.87KB |
| 41 |
486.08KB |
| 42 |
440.83KB |
| 43 |
182.60KB |
| 44 |
789.97KB |
| 45 |
1007.19KB |
| 46 |
867.05KB |
| 47 |
912.04KB |
| 48 |
339.95KB |
| 49 |
357.71KB |
| 5 |
503.72KB |
| 5.1 Faster-r-cnn.pdf |
743.83KB |
| 5. Conv2D Layer in Tensorflow 2-Keras.mp4 |
86.53MB |
| 5. Faster R-CNN.mp4 |
75.02MB |
| 5. Faster R-CNN.srt |
14.41KB |
| 5. Labeling data with LabelImg.mp4 |
80.82MB |
| 5. Labeling data with LabelImg.srt |
10.48KB |
| 5. Regularization.mp4 |
70.65MB |
| 5. Regularization.srt |
8.53KB |
| 50 |
879.31KB |
| 51 |
889.99KB |
| 52 |
939.73KB |
| 53 |
98.01KB |
| 54 |
1012.04KB |
| 55 |
416.38KB |
| 56 |
213.39KB |
| 57 |
320.67KB |
| 58 |
705.89KB |
| 59 |
42.95KB |
| 6 |
607.28KB |
| 6.1 ssd.pdf |
2.20MB |
| 6. Activation Functions.mp4 |
86.91MB |
| 6. Activation Functions.srt |
13.48KB |
| 6. Max Pooling.mp4 |
35.31MB |
| 6. Max Pooling.srt |
7.69KB |
| 6. SSD (Single Shot Detector).mp4 |
160.23MB |
| 6. SSD (Single Shot Detector).srt |
21.73KB |
| 60 |
158.92KB |
| 61 |
711.12KB |
| 62 |
197.62KB |
| 63 |
894.00KB |
| 64 |
420.04KB |
| 65 |
663.29KB |
| 66 |
345.28KB |
| 67 |
971.39KB |
| 68 |
1001.11KB |
| 69 |
1001.11KB |
| 7 |
415.32KB |
| 7. Evaluating Activation Functions with Keras.mp4 |
88.82MB |
| 7. Evaluating Activation Functions with Keras.srt |
13.78KB |
| 7. ReLU function.mp4 |
50.01MB |
| 7. ReLU function.srt |
5.47KB |
| 7. TensorFlow2 Object Detection API on images and videos.mp4 |
168.59MB |
| 7. TensorFlow2 Object Detection API on images and videos.srt |
22.53KB |
| 70 |
248.82KB |
| 71 |
675.38KB |
| 72 |
724.27KB |
| 73 |
817.41KB |
| 74 |
744.67KB |
| 75 |
862.30KB |
| 8 |
96.56KB |
| 8. Batch Normalization.mp4 |
95.63MB |
| 8. Batch Normalization.srt |
8.11KB |
| 8. Multilayer Perceptron with Keras.mp4 |
102.41MB |
| 8. Multilayer Perceptron with Keras.srt |
13.85KB |
| 8. Train Blood Cells Dataset in TensorFlow Object Detection part1.mp4 |
101.64MB |
| 8. Train Blood Cells Dataset in TensorFlow Object Detection part1.srt |
13.23KB |
| 9 |
156.54KB |
| 9. DropOut.mp4 |
38.84MB |
| 9. DropOut.srt |
4.27KB |
| 9. Train Blood Cells Dataset in TensorFlow Object Detection part2.mp4 |
176.41MB |
| 9. Train Blood Cells Dataset in TensorFlow Object Detection part2.srt |
20.50KB |
| TutsNode.com.txt |
63B |