Resources
I love creating and sharing learning resources and speaking about what I work on. Below are some of the learning resources I have created.
Videos
Code and Tutorials
Deep Learning for Computer Vision Package
Deep Learning for Computer Vision covers foundations of computer vision and deep learning, state-of-the-arts visual architectures(such as ConvNets and Vision Transformers), various Computer Vision tasks(such as image classification, object detection and segmentation), tips and tricks for training and analyzing visual recognition systems.
Complete Machine Learning Package
[Web] [Github] [Nbviewer] [Colab]
Complete Machine Learning Package is a comprehensive repository containing 30+ notebooks on Python programming, data manipulation, data analysis, data visualization, data cleaning, classical machine learning, Computer Vision and Natural Language Processing(NLP).
Modern Convolutional Neural Network Architectures(ModernConvNets)
Revision of the designs, implementations, and annotated papers of 13 Modern Convolutional Neural Network architectures: AlexNet, GoogLeNet(Inceptionv1), ResNet, ResNeXt, Xception, DenseNet, MobileNetV1, MobileNetV2, EfficientNet, RegNet, ConvMixer, ConvNeXt.