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Course content
Sections:
1
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Activities:
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Resources:
86
- 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