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Master Deep Learning for Computer Vision in TensorFlow(2024)
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Dec 2024
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Section 1
Introduction
001 Welcome Ui40 gitir
002 General Introduction EEO6 gitir
003 Course Content hYwp gitir
006 Tensor Basics nAEc gitir
007 Tensor Initialization and Casting cNva gitir
008 Indexing ASiI gitir
009 Maths Operations in Tensorflow DhVY gitir
010 Linear Algebra Operations in Tensorflow wCZh gitir
011 Common Tensorflow Methods tSWc gitir
012 Ragged Tensors K3y6 gitir
013 Sparse Tensors QFhK gitir
014 String Tensors NkDN gitir
015 Tensorflow Variables GEWt gitir
018 Task Understanding Wra6 gitir
019 Data Preparation 4FzU gitir
020 Linear Regression Model 0IJT gitir
021 Error Sanctioning Nez2 gitir
022 Training and Optimization 6UJi gitir
023 Performance Measurement oXCS gitir
024 Validation and Testing a5UX gitir
025 Corrective Measures tMBo gitir
026 TensorFlow Datasets Olms gitir
028 Task Understanding 7ns0 gitir
029 Data Preparation kM2d gitir
030 Data Visualization bOme gitir
031 Data Processing OmHi gitir
032 How and Why Convolutional Neural Networks work A5H4 gitir
033 Building Convnets in Tensorflow niwZ gitir
034 Binary Crossentropy Loss iinO gitir
035 Convnet Training sxUs gitir
036 Model Evaluation and Testing fdG1 gitir
037 Loading and Saving Tensorflow Models to Google Drive Fo3C gitir
038 Functional API oDU5 gitir
039 Model Subclassing vg3R gitir
040 Custom Layers WZgl gitir
041 Precision Recall and Accuracy ppxE gitir
042 Confusion Matrix 3226 gitir
043 ROC Curve gsWb gitir
044 Tensorflow Callbacks T4KS gitir
045 Learning rate scheduling Atqp gitir
046 Model checkpointing hF27 gitir
047 Mitigating Overfitting and Underfitting with Dropout Regularization wtWK gitir
048 Data augmentation with TensorFlow using tf image and Keras Layers mQpR gitir
049 Mixup Data augmentation with TensorFlow 2 with intergration in tf data 6Ann gitir
050 Cutmix Data augmentation with TensorFlow 2 and intergration in tf data PBXY gitir
051 Albumentations with TensorFlow 2 and PyTorch for Data augmentation YNcm gitir
052 Custom Loss and Metrics y7m6 gitir
053 Eager and Graph Modes zVdd gitir
054 Custom Training Loops Qqmx gitir
055 Data Logging v1vn gitir
056 Viewing Model Graphs JAVs gitir
057 Hyperparameter tuning 9Bbw gitir
058 Profiling and other visualizations with Tensorboard 2HMA gitir
059 Experiment Tracking 8aHE gitir
060 Hyperparameter Tuning with Weights and Biases and TensorFlow 2 vTpm gitir
061 Dataset Versioning with Weights and Biases and TensorFlow 2 z4aF gitir
062 Data Versioning with Wandb 7MTM gitir
063 Model Versioning with Weights and Biases and TensorFlow 2 VHQ3 gitir
065 Data Preparation UZdL gitir
066 Modeling and Training Eqz2 gitir
067 Data augmentation KAbd gitir
068 Tensorflow Records l8jx gitir
069 Alexnet GbWD gitir
070 Vggnet YKtk gitir
071 Resnet FLOV gitir
072 Coding Resnet FdoD gitir
073 Mobilenet ony1 gitir
074 Efficientnet Bpbl gitir
075 Leveraging Pretrained Models kpLc gitir
076 Finetuning mHam gitir
077 Visualizing intermediate layers ZmM7 gitir
078 Grad cam Method Vepa gitir
079 Ensembling P2MN gitir
080 Class Imbalance rAz3 gitir
081 Understanding VITs 3B3E gitir
082 Building VITs from scratch iWRf gitir
083 Finetuning Huggingface Transformers JNs7 gitir
084 Model Evaluation with Wandb o62f gitir
085 Data efficient transformers FqqF gitir
086 Swin Transformers wCjm gitir
087 Model Conversion from Tensorflow to Onnx tTFo gitir
088 Understanding quantization 3LwN gitir
089 Practical quantization of Onnx model TTrA gitir
090 Quantization Aware training WdRj gitir
091 Conversion to Tensorflow lite model 0P7O gitir
092 What is an API Co5K gitir
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Master Deep Learning for Computer Vision in TensorFlow(2024)
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15 Dec 2024
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