22.21 GB | 1h 4min 27s | mp4 | 1280X720  | 16:9
Genre:eLearning |Language:English

Files Included :
1  Welcome.mp4 (21.29 MB)
2  General Introduction.mp4 (222.86 MB)
3  Course Content.mp4 (77.74 MB)
1  Data Logging.mp4 (287.15 MB)
2  Viewing Model Graphs.mp4 (21.5 MB)
3  Hyperparameter tuning.mp4 (194.95 MB)
4  Profiling and other visualizations with Tensorboard.mp4 (69.23 MB)
1  Experiment Tracking.mp4 (469.67 MB)
2  Hyperparameter Tuning with Weights and Biases and TensorFlow 2.mp4 (186.11 MB)
3  Dataset Versioning with Weights and Biases and TensorFlow 2.mp4 (329.36 MB)
4  Data Versioning with Wandb.mp4 (329.5 MB)
5  Model Versioning with Weights and Biases and TensorFlow 2.mp4 (137.45 MB)
2  Data Preparation.mp4 (225.41 MB)
3  Modeling and Training.mp4 (371.79 MB)
4  Data augmentation.mp4 (142.09 MB)
5  Tensorflow Records.mp4 (293.65 MB)
1  Alexnet.mp4 (183.52 MB)
2  Vggnet.mp4 (116.45 MB)
3  Resnet.mp4 (351.48 MB)
4  Coding Resnet.mp4 (180.36 MB)
5  Mobilenet.mp4 (206.77 MB)
6  Efficientnet.mp4 (189.24 MB)
1  Leveraging Pretrained Models.mp4 (163.38 MB)
2  Finetuning.mp4 (112.17 MB)
1  Visualizing intermediate layers.mp4 (157.97 MB)
2  Grad-cam Method.mp4 (226.85 MB)
1  Ensembling.mp4 (45.22 MB)
2  Class Imbalance.mp4 (100.61 MB)
1  Understanding VITs.mp4 (421.93 MB)
2  Building VITs from scratch.mp4 (398.59 MB)
3  Finetuning Huggingface Transformers.mp4 (206.49 MB)
4  Model Evaluation with Wandb.mp4 (140.23 MB)
5  Data efficient transformers.mp4 (72.86 MB)
6  Swin Transformers.mp4 (192.31 MB)
1  Model Conversion from Tensorflow to Onnx.mp4 (205.38 MB)
2  Understanding quantization.mp4 (159.78 MB)
3  Practical quantization of Onnx model.mp4 (64.99 MB)
4  Quantization Aware training.mp4 (160.52 MB)
5  Conversion to Tensorflow lite model.mp4 (154.58 MB)
6  What is an API.mp4 (127.97 MB)
7  Building the Emotions Detection API with Fastapi.mp4 (674.71 MB)
8  Deploy the Emotions Detection API to the Cloud.mp4 (103.37 MB)
9  Load tesing the Emotions Detection API with Locust.mp4 (106.28 MB)
2  Understanding object detection.mp4 (52.42 MB)
3  YOLO Paper.mp4 (571.91 MB)
4  Dataset Preparation.mp4 (401 MB)
5  YOLO Resnet.mp4 (53.95 MB)
6  YOLO Loss.mp4 (691.12 MB)
7  Data augmentation.mp4 (219.2 MB)
8  Testing.mp4 (308.94 MB)
9  Data generators.mp4 (51.43 MB)
10  String Tensors.mp4 (29.49 MB)
11  Tensorflow Variables.mp4 (25.62 MB)
2  Tensor Basics.mp4 (33.14 MB)
3  Tensor Initialization and Casting.mp4 (306.74 MB)
4  Indexing.mp4 (157.44 MB)
5  Maths Operations in Tensorflow.mp4 (217.22 MB)
6  Linear Algebra Operations in Tensorflow.mp4 (381.47 MB)
7  Common Tensorflow Methods.mp4 (214.15 MB)
8  Ragged Tensors.mp4 (96.8 MB)
9  Sparse Tensors.mp4 (19.48 MB)
10  Model Evaluation with FiftyOne.mp4 (258.54 MB)
11  Virtual Cloth Try-on with Stable Diffusion Inpainting.mp4 (218.75 MB)
12  Building FiftyOne Data Augmentation Plugin with Stable Diffusion Inpainting.mp4 (556.54 MB)
2  Problem Understanding.mp4 (35.83 MB)
3  Data Downloading.mp4 (35.11 MB)
4  Data Splitting.mp4 (118.89 MB)
5  Data Processing.mp4 (178.72 MB)
6  Data Visualization with Matplotlib.mp4 (69.72 MB)
7  Data Visualization with FiftyOne.mp4 (184.92 MB)
8  Understanding Segformer.mp4 (190.77 MB)
9  Model Creation.mp4 (183.3 MB)
2  People Counting - Shangai Tech Dataset.mp4 (83.51 MB)
3  Dataset Preparation.mp4 (323.88 MB)
4  CSRNET.mp4 (75.34 MB)
5  Training and Optimization.mp4 (51.85 MB)
6  Data Augmentation.mp4 (260.93 MB)
2  Introduction to Image generation.mp4 (27.26 MB)
3  Understanding Variational autoencoders.mp4 (117.51 MB)
4  VAE training and digit generation.mp4 (299.23 MB)
5  Latent space visualizations.mp4 (112.88 MB)
6  How GANs work.mp4 (232.5 MB)
7  The GAN Loss.mp4 (163.18 MB)
8  Improving GAN training.mp4 (168.74 MB)
9  Face generation with GANs.mp4 (411.8 MB)
1  Python Installation.mp4 (18.15 MB)
10  Encapsulation.mp4 (11.58 MB)
11  Polymorphism.mp4 (13.41 MB)
12  Decorators.mp4 (90.77 MB)
13  Generators.mp4 (46.59 MB)
14  Numpy Package.mp4 (207.96 MB)
15  Matplotlib Introduction.mp4 (21.53 MB)
2  Conditional Statements.mp4 (89.57 MB)
3  Variables and Basic Operators.mp4 (134.99 MB)
4  Loops.mp4 (93.23 MB)
5  Methods.mp4 (88.44 MB)
6  Objects and Classes.mp4 (59.14 MB)
7  Operator Overloading.mp4 (52.9 MB)
8  Method Types.mp4 (48.35 MB)
9  Inheritance.mp4 (57.33 MB)
10  Corrective Measures.mp4 (80.25 MB)
11  TensorFlow Datasets.mp4 (79.43 MB)
3  Task Understanding.mp4 (23.56 MB)
4  Data Preparation.mp4 (224.68 MB)
5  Linear Regression Model.mp4 (101.06 MB)
6  Error Sanctioning.mp4 (107.8 MB)
7  Training and Optimization.mp4 (132.36 MB)
8  Performance Measurement.mp4 (27.3 MB)
9  Validation and Testing.mp4 (178.06 MB)
10  Model Evaluation and Testing.mp4 (29.58 MB)
11  Loading and Saving Tensorflow Models to Google Drive.mp4 (128.9 MB)
2  Task Understanding.mp4 (56.87 MB)
3  Data Preparation.mp4 (155.88 MB)
4  Data Visualization.mp4 (18.8 MB)
5  Data Processing.mp4 (39.52 MB)
6  How and Why Convolutional Neural Networks work.mp4 (348.61 MB)
7  Building Convnets in Tensorflow.mp4 (44.7 MB)
8  Binary Crossentropy Loss.mp4 (57.44 MB)
9  Convnet Training.mp4 (64.63 MB)
1  Functional API.mp4 (138.4 MB)
2  Model Subclassing.mp4 (119.54 MB)
3  Custom Layers.mp4 (135.7 MB)
1  Precision,Recall and Accuracy.mp4 (211.32 MB)
2  Confusion Matrix.mp4 (62.37 MB)
3  ROC Curve.mp4 (50.19 MB)
1  Tensorflow Callbacks.mp4 (217.44 MB)
2  Learning rate scheduling.mp4 (136.87 MB)
3  Model checkpointing.mp4 (61.83 MB)
4  Mitigating Overfitting and Underfitting with Dropout, Regularization.mp4 (202 MB)
1  Data augmentation with TensorFlow using tf image and Keras Layers.mp4 (475.19 MB)
2  Mixup Data augmentation with TensorFlow 2 with intergration in tf data.mp4 (161.77 MB)
3  Cutmix Data augmentation with TensorFlow 2 and intergration in tf data.mp4 (344.06 MB)
4  Albumentations with TensorFlow 2 and PyTorch for Data augmentation.mp4 (197.33 MB)
1  Custom Loss and Metrics.mp4 (176.01 MB)
2  Eager and Graph Modes.mp4 (88.69 MB)
3  Custom Training Loops.mp4 (234.98 MB)]
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