PyTorch-Intuition & Practise

This repo is dedeicated to learn regarding PyTorch in Deep Learning domain. Each concept is tried to implement using PyTorch Framework.

ANN PART

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0 . Basic Functionalities of Torch(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Torch_postmortem.ipynb)

1 . DataLoader Liabray determines - batch size data which is used to train the model. (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/2_Pytorch_DataLoader.ipynb)

2 . Create the model with calling nn.Module(Class) (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/ANN_architecture_calling_nn_Module.ipynb)

3 . Training the model with the previous architecture(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Train_ANN_with_calling_simple_nn_Module.ipynb)

4 . Weight Initialization(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Airline_Prediction_weight_Initialization.ipynb)

5 . Comparision with TensorFlow & PyTorch Model(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Comparison_with_Tensorflow_with_PyTorch_.ipynb)

6 . Create an Simple model with KFold - 5 (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Simmple_ANN_architecture_with_KFold_5.ipynb)

7 . Introduce the Dropout Layer (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Simmple_ANN_architecture_with_KFold_5_with_Dropout.ipynb)

8 . Regularization (L1 & L2) : (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Regularization_L1_%26_L2_in_Pytorch.ipynb)

9 . Batch Normalization (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Batch_Normalization.ipynb)

10 . Early stopping(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Early_Stopping_in_PyTorch.ipynb)

11 . Check point Initialization(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Model_Checkpoint_in_PyTorch.ipynb)

12 . Regression Problem (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Regression_in_PyTorch.ipynb)

13 . Simple Project on Classification(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Airline%20(1).ipynb)

14 . Simple project on Regression(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Regression_project_in_PyTorch.ipynb)

15 . CUDA/GPU Initization(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/GPU_CUDA_connect_in_PyTorch.ipynb)

16.1 . Simple Sequential Model Intuition(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Create_a_sequential_model_in_PyTorch.ipynb)

16.2 . Simple Sequential Model Intuition ...(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Create_a_sequential_model_in_PyTorch_new.ipynb)

16.3 Simple Sequential Model Intuition ...(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Crab_age_prediction_in_Pytorch.ipynb)

CNN PART

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1. Simple CNN architecture without calling Sequential & GPU (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Simple_CNN_architecture_without_calling_Sequential_model_in_PyTorch.ipynb)

2. Simple CNN architecture with Calling GPU(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Simple_CNN_architecture_with_calling_GPU_in_PyTorch.ipynb)

3. Create Sequential Model(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Sequential_CNN_model_in_PyTorch.ipynb)

4. Transfer Learning(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Functional_API_type_model_in_PyTorch_%2B_Transfer_Learning.ipynb)

5. Project(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Project_CNN_Malaria_Disease_Classification_using_PyTorch_%26_TensorFlow.ipynb) & (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Project_CNN_Malaria_Disease_Classification_using_PyTorch_%26_TensorFlow_Final.ipynb)

6. Project - 2: Ensemple Approach with FAPI aslike (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Ensemble_Approach.ipynb) & (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Chicken_Pox_Classification_in_PyTorch_Ensemble_Approach.ipynb)

7. TensorFlow Functional API type Model in PyTorch(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Functional_API_alike_in_PyTorch.ipynb) & (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Functional_API_type_model_in_PyTorch.ipynb)

8. Data Augmentation Task(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/LAST%20(1).ipynb)

9. Residual Block (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Residual_Block.ipynb)

10. Conv1d

GAN

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1. Simple GAN(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/Vanilla_GAN_in_PyTorch.ipynb)

2. MNIST GAN(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/MINIST_GAN_in_PyTorch.ipynb)

3. DGGAN implementation(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/DGGAN_Image_Generation_in_PyTorch_updated.ipynb)

4. CGAN implementation(https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/CGAN.ipynb)

5. WGAN (https://github.com/atikul-islam-sajib/GPWGAN)

6. InfoGAN (https://github.com/atikul-islam-sajib/InfoGAN)

7. LSGAN (https://github.com/atikul-islam-sajib/LSGAN)

8. ACGAN (https://github.com/atikul-islam-sajib/AC-GAN)

9. SGAN (https://github.com/atikul-islam-sajib/SGAN)

10. Pix2Pix (https://github.com/atikul-islam-sajib/pix2pix)

11. SRGAN (https://github.com/atikul-islam-sajib/SRGAN)

12. CycleGAN (https://github.com/atikul-islam-sajib/CycleGAN)

13. DiscoGAN (https://github.com/atikul-islam-sajib/DiscoGAN)

14. DualGAN (https://github.com/atikul-islam-sajib/DualGAN)

15. SeqGAN (https://github.com/atikul-islam-sajib/PyTorch-Intuition/blob/main/seGAN.ipynb)

RNN PART

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1. RNN & LSTM

2. Bidirectional LSTM & GRU

3. Project - Sentimental Classification