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| [TGx]Downloaded from torrentgalaxy.to .txt |
585B |
| 0 |
1.06MB |
| 1 |
501.23KB |
| 10 |
1.31MB |
| 10 - Sparse Tensors.mp4 |
18.03MB |
| 11 |
1.80MB |
| 11 - String Tensors.mp4 |
23.02MB |
| 12 |
563.93KB |
| 12 - Variables.mp4 |
44.94MB |
| 13 |
952.62KB |
| 13 - Understanding the Task.mp4 |
30.55MB |
| 14 |
364.36KB |
| 14 - Data Preparation.mp4 |
276.34MB |
| 15 |
795.06KB |
| 15 - Linear Regression Model.mp4 |
105.13MB |
| 16 |
1.66MB |
| 16 - Error Sanctioning.mp4 |
95.16MB |
| 17 |
1.82MB |
| 17 - Training and Optimization.mp4 |
116.68MB |
| 18 |
1.12MB |
| 18 - Performance Measurement.mp4 |
21.96MB |
| 19 |
1.19MB |
| 19 - Validation and Testing.mp4 |
135.69MB |
| 1 - Welcome.mp4 |
32.05MB |
| 2 |
367.20KB |
| 20 |
561.81KB |
| 20 - Corrective Measures.mp4 |
195.84MB |
| 21 |
1.32MB |
| 21 - Understanding the Task.mp4 |
63.76MB |
| 22 |
663.58KB |
| 22 - Data Preparation.mp4 |
160.60MB |
| 23 |
981.71KB |
| 23 - Data Visualization.mp4 |
16.84MB |
| 24 |
632.64KB |
| 24 - Data Processing.mp4 |
54.47MB |
| 25 |
1.23MB |
| 25 - How and Why Convolutional Neural Networks Work.mp4 |
348.69MB |
| 26 |
1.44MB |
| 26 - Building ConvNets with TensorFlow.mp4 |
44.70MB |
| 27 |
585.17KB |
| 27 - Binary Crossentropy Loss.mp4 |
47.15MB |
| 28 |
1.87MB |
| 28 - Training.mp4 |
113.73MB |
| 29 |
1.88MB |
| 29 - Model Evaluation and Testing.mp4 |
39.69MB |
| 2 - General Introduction.mp4 |
202.13MB |
| 3 |
1.97MB |
| 30 |
161.63KB |
| 30 - Loading and Saving tensorflow models to gdrive.mp4 |
128.91MB |
| 31 |
1.03MB |
| 31 - Functional API.mp4 |
138.42MB |
| 32 |
1.76MB |
| 32 - Model Subclassing.mp4 |
119.56MB |
| 33 |
840.76KB |
| 33 - Custom Layers.mp4 |
135.67MB |
| 34 |
728.38KB |
| 34 - PrecisionRecallAccuracy.mp4 |
211.38MB |
| 35 |
1.70MB |
| 35 - Confusion Matrix.mp4 |
62.32MB |
| 36 |
1.92MB |
| 36 - ROC curve.mp4 |
50.20MB |
| 37 |
560.18KB |
| 37 - Callbacks with TensorFlow.mp4 |
217.35MB |
| 38 |
147.15KB |
| 38 - Learning Rate Scheduling.mp4 |
136.79MB |
| 39 |
1.40MB |
| 39 - Model Checkpointing.mp4 |
61.80MB |
| 3 - Basics.mp4 |
43.54MB |
| 4 |
47.65KB |
| 40 |
1.47MB |
| 40 - Mitigating Overfitting and Underfitting with Dropout Regularization.mp4 |
202.12MB |
| 41 |
1.92MB |
| 41 - Data augmentation with TensorFlow using tfimage and Keras Layers.mp4 |
424.03MB |
| 42 |
1.31MB |
| 42 - Mixup Data augmentation with TensorFlow 2 with intergration in tfdata.mp4 |
161.86MB |
| 43 |
1.81MB |
| 43 - Cutmix Data augmentation with TensorFlow 2 and intergration in tfdata.mp4 |
344.20MB |
| 44 |
1.80MB |
| 44 - Albumentations with TensorFlow 2 and PyTorch for Data augmentation.mp4 |
617.51MB |
| 45 |
1.58MB |
| 45 - Custom Loss and Metrics in TensorFlow 2.mp4 |
176.08MB |
| 46 |
582.71KB |
| 46 - Eager and Graph Modes in TensorFlow 2.mp4 |
88.71MB |
| 47 |
1.21MB |
| 47 - Custom Training Loops in TensorFlow 2.mp4 |
234.88MB |
| 48 |
313.78KB |
| 48 - Log data.mp4 |
287.22MB |
| 49 |
342.80KB |
| 49 - view model graphs.mp4 |
21.49MB |
| 4 - Initialization and Casting.mp4 |
406.53MB |
| 5 |
1.47MB |
| 50 |
1.09MB |
| 50 - hyperparameter tuning.mp4 |
194.97MB |
| 51 |
82.38KB |
| 51 - Profiling and other visualizations with Tensorboard.mp4 |
69.15MB |
| 52 |
455.62KB |
| 52 - Experiment Tracking.mp4 |
469.64MB |
| 53 |
1.32MB |
| 53 - Hyperparameter Tuning with Weights and Biases and TensorFlow 2.mp4 |
222.68MB |
| 54 |
1.57MB |
| 54 - Dataset Versioning with Weights and Biases and TensorFlow 2.mp4 |
329.45MB |
| 55 |
276.91KB |
| 55 - Model Versioning with Weights and Biases and TensorFlow 2.mp4 |
137.43MB |
| 56 |
1.79MB |
| 56 - data preparation.mp4 |
225.45MB |
| 57 |
1.65MB |
| 57 - Modeling and Training.mp4 |
371.89MB |
| 58 |
887.00KB |
| 58 - Data augmentation.mp4 |
142.19MB |
| 59 |
1.36MB |
| 59 - Tensorflow records.mp4 |
293.64MB |
| 5 - Indexing.mp4 |
77.57MB |
| 6 |
1.40MB |
| 60 |
1.78MB |
| 60 - Alexnet.mp4 |
183.29MB |
| 61 |
860.05KB |
| 61 - vggnet.mp4 |
116.43MB |
| 62 |
1.29MB |
| 62 - resnet.mp4 |
351.78MB |
| 63 |
1.52MB |
| 63 - coding resnet.mp4 |
180.30MB |
| 64 |
442.60KB |
| 64 - mobilenet.mp4 |
206.77MB |
| 65 |
1.19MB |
| 65 - efficientnet.mp4 |
189.18MB |
| 66 |
867.16KB |
| 66 - Pretrained Models.mp4 |
163.45MB |
| 67 |
1.02MB |
| 67 - Finetuning.mp4 |
112.21MB |
| 68 |
247.90KB |
| 68 - visualizing intermediate layers.mp4 |
158.08MB |
| 69 |
1.68MB |
| 69 - gradcam method.mp4 |
226.81MB |
| 6 - Maths Operations.mp4 |
215.04MB |
| 7 |
115.04KB |
| 70 |
205.32KB |
| 70 - Ensembling.mp4 |
45.25MB |
| 71 |
1.53MB |
| 71 - Class imbalance.mp4 |
100.64MB |
| 72 |
1.80MB |
| 72 - Understanding VITs.mp4 |
421.95MB |
| 73 |
872.48KB |
| 73 - Building VITs from scratch.mp4 |
398.60MB |
| 74 |
768.43KB |
| 74 - Finetuning Huggingface VITs.mp4 |
206.56MB |
| 75 |
1.06MB |
| 75 - Model Evaluation with Wandb.mp4 |
140.20MB |
| 76 |
1.30MB |
| 76 - Data efficient Transformers.mp4 |
72.81MB |
| 77 |
468.38KB |
| 77 - Swin Transformers.mp4 |
192.24MB |
| 78 |
317.01KB |
| 78 - Conversion from tensorflow to Onnx Model.mp4 |
205.43MB |
| 79 |
1.95MB |
| 79 - Understanding quantization.mp4 |
268.18MB |
| 7 - Linear Algebra Operations.mp4 |
371.50MB |
| 8 |
508.17KB |
| 80 |
1.45MB |
| 80 - Practical quantization of Onnx Model.mp4 |
64.98MB |
| 81 |
1002.17KB |
| 81 - Quantization Aware training.mp4 |
160.53MB |
| 82 |
45.43KB |
| 82 - Conversion to tensorflowlite model.mp4 |
154.69MB |
| 83 |
526.72KB |
| 83 - How APIs work.mp4 |
127.92MB |
| 84 |
1.97MB |
| 84 - Building API with Fastapi.mp4 |
674.94MB |
| 85 - Deploying API to the Cloud.mp4 |
100.22MB |
| 86 - Load testing API.mp4 |
106.35MB |
| 8 - Common Methods.mp4 |
299.07MB |
| 9 |
227.44KB |
| 9 - RaggedTensors.mp4 |
78.48MB |
| TutsNode.net.txt |
63B |