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convolutional_neural_network_on_coco_dataset

Images belonging to 10 classes from COCO dataset are used to perform classification using 3 different CNNs.

coronavirus

In this project, we study the effect of face masks on the death rate due to COVID-19 using different Machine Learning algorithms.

deep_learning_on_imagenet_dataset

Images belonging to different classes are downloaded from ImageNet, and a simple neural network is trained and tested on them for classification.

multi_fidelity_gaussian_processes

A recursive version of Multi Fidelity Gaussian processes is implemented to eliminate the need for running numerous high-fidelity level (fine grid) simulations.

object_detection_and_localization_on_coco_dataset

A deep neural network comprising of residual blocks with a custom architecture is designed for single object detection and localization in COCO images.

recurrent_neural_network_for_text_classification

Various kinds of RNNs with different approaches are used to distinguish the positive users' reviews from negative ones provided by Amazon.

uncertainty_quantification_course

user-based_machine_learning

The user defines a set of features and an output to perform a regression task.

yolo_like_detector

A YOLO-like detector for the detection and localization of multiple objects in COCO images is proposed.

yolov5_on_a_custom_dataset

A detailed demo of YOLOv5 implementation to train and test a custom dataset is presented.