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Machine Learning Basics
A practical set of notebooks on machine learning basics, implemented in both TF2.0 + Keras and PyTorch.
deep-learning natural-language-processing tensorflow pytorch
Hands On Machine Learning
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and ...
scikit-learn tensorflow keras tutorial
A Visual Guide to Recurrent Layers in Keras
Understand how to use Recurrent Layers like RNN, GRU and LSTM in Keras with diagrams.
recurrent-neural-networks lstm keras tensorflow
Test-Time Data Augmentation
Tutorial on how to properly implement test-time image data augmentation in a production environment with limited computational resources.
data-augmentation keras production tensorflow
SimpleGAN
A Tensorflow-based framework to ease the training of generative models
computer-vision generative-adversarial-networks tensorflow deep-learning
Torchlayers
Shape inference for PyTorch (like Keras) & new layers
pytorch library inference shape
Object Detection with RetinaNet
Implementing RetinaNet: Focal Loss for Dense Object Detection.
object-detection retinanet keras tensorflow
Keras Debugging Tips
Four simple tips to help you debug your Keras code.
debugging tensorflow keras tutorial
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