Pinned Repositories
AGU2017
Content for my AGU 2017 presentations.
batch-shipyard
Provision, execute, and monitor batch and HPC container workloads on Azure Batch
breast_cancer_classifier
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
caffe
This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors (HSW+) and Intel® Xeon Phi processors
coronavirus_data
darknet
YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )
Deep-Learning-for-Satellite-Imagery
Deep learning courses and projects
predicting-poverty
Combining satellite imagery and machine learning to predict poverty
tomassa's Repositories
tomassa/breast_cancer_classifier
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
tomassa/coronavirus_data
tomassa/darknet
YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )
tomassa/fastai-v3
Starter app for fastai v3 model deployment on Render
tomassa/fastbook
Draft of the fastai book
tomassa/gid_scripts
tomassa/hello-world
tutorial
tomassa/image_tabular
Integrate image and tabular data for deep learning
tomassa/many-to-many-dijkstra
A predictive model developed to identify medium-voltage electrical distribution grid infrastructure using publicly available data sources.
tomassa/ML-DL-Projects
Personal projects using machine learning and deep learning techniques
tomassa/my-gh-importer-labs
my-gh-importer-labs
tomassa/notes
tomassa/ObjectDetection
Some experiments with object detection in PyTorch
tomassa/osmnx-examples
Examples, demos, and tutorials demonstrating the usage of OSMnx
tomassa/pangeo-example-notebooks
Jupyter notebooks for use with pangeo-data/helm-chart
tomassa/Practical-Deep-Learning-For-Coders
Material for my run of Fast.AI
tomassa/pretrained-models.pytorch
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
tomassa/satellite-image-deep-learning
Resources for performing deep learning on satellite imagery
tomassa/streamlit-example
Example Streamlit app that you can fork to test out share.streamlit.io
tomassa/timeseries_fastai
fastai V2 implementation of Timeseries classification papers.
tomassa/timeseriesAI
Practical Deep Learning for Time Series / Sequential Data library based on fastai v2/ Pytorch
tomassa/TreeTect
Tree detection
tomassa/xview-yolov3
xView 2018 Object Detection Challenge: YOLOv3 Training and Inference.
tomassa/xView2_baseline
Baseline localization and classification models for the xView 2 challenge.
tomassa/xView3-The-First-Place-Solution
Contains source code for the winning solution of the xView3 challenge https://iuu.xview.us/.
tomassa/xView3_second_place
XView3 challenge, 2nd place solution
tomassa/yolo_dataprep
tomassa/yolov3
Fork of Ultralytics YoloV3 with FastAI for augmentation, learning rate finding, jupyter training, and export to TensorFlow Lite
tomassa/yolov3-1
YOLOv3 in PyTorch > ONNX > CoreML > TFLite
tomassa/zanzibar-aerial-mapping
Open source notebooks to create state-of-the-art detection, segmentation, & classification of buildings on drone/aerial imagery with deep learning