Repository contains variour Machine learning , Deep learning and computer vision approaches
Notebook Covers following
- Loading image using opencv
- Using filter for Edge computation
- Feature extraction and visualization using HOG.
Notebook Cover following
- Loading images
- Image visualization with segemenation
- Feature extraction using Pyradiomics
Notebook Covers following
- Loading dataset into csv format(Heart disease dataset for logistic regression and diabetes dataset for linear regression)
- converting pandas dataframe to tf.data format
- Convarience matrix calculation
- Training linear regression using Sklearn
- Training logistic regresison using tensorflow
Notebook Covers following
- Loading dataset in csv format
- Training SVM with Grid Search
- Model evaluation
Notebook covers following
- Loading data from directory using flow_from_dir function
- Data augmentation using ImageDatagenerator
- Validation split from same dataset
- Train ResNet50 as Backbone
- Evaluating the Model
Notebook covers following
- Loading data with csv file and directory
- Data Visualization
- ResNet 50 , Xception Net and NASNet as backbone for Fine Tuning
- Data loader with Augmentation
- Confusion metrics for evaluation
Notebook covers following
- Loading images from folder custom data loader
- EfficientNet as Unet backbone
- Loss function IOU Dice
- Custom callback for evalauting on test set while training
- Segmentation visualization
- evalaution
Notebook covers following
- Loading image from directory
- Custom Encoder and Decoder
- KL and mse loss
- visualization
- evalaution
Notebook covers following
- Uses cancer stage classification dataset
- Training DNN model
- Hyper-parametert tuning
- visualization
- Evaluation