Rebeen Ali Hamad's repositories
tf-simple-metric-learning
Simple metric learning methods via tf.keras
computervision-recipes
Best Practices, code samples, and documentation for Computer Vision.
EffectivePyTorch
PyTorch tutorials and best practices.
EffectiveTensorflow
TensorFlow 1.x and 2.x tutorials and best practices.
frcnn_medium_sample
Sample code and data for Medium post on https://medium.com/fullstackai/how-to-train-an-object-detector-with-your-own-coco-dataset-in-pytorch-319e7090da5
Imbalanced-Data-with-SMOTE-Techniques
This repository contains implementation of some techniques like SMOTE, ADASYN, SMOTE + Tomek Links, SMOTE + ENN to overcome class imbalance in a binary classification problem.
MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
ml_playground
Collection of machine learning projects
mobilenetv3-1
mobilenetv3 with pytorch，provide pre-train model
python-machine-learning-book-3rd-edition
The "Python Machine Learning (3rd edition)" book code repository
pytorch-cifar
95.16% on CIFAR10 with PyTorch
pytorch-deep-learning
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
Pytorch-how-and-when-to-use-Module-Sequential-ModuleList-and-ModuleDict
Code for my medium article
pytorch-image-classification
Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision. [IN PROGRESS]
pytorch-ssd
MobileNetV1, MobileNetV2, VGG based SSD/SSD-lite implementation in Pytorch 1.0 / Pytorch 0.4. Out-of-box support for retraining on Open Images dataset. ONNX and Caffe2 support. Experiment Ideas like CoordConv.
smote_variants
A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features
SSD
High quality, fast, modular reference implementation of SSD in PyTorch
t81_558_deep_learning
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
time_series_augmentation
An example of time series augmentation methods with Keras
traffic-sign-recognition
Built and trained a deep neural network to classify traffic signs, using PyTorch. The highlights of this solution would be data preprocessing, trained with heavily augmented data and using Spatial Transformer Network.
transferlearning
Everything about Transfer Learning and Domain Adaptation--迁移学习