utkarshshukla2912 / ML-CPP

List of ML models and DL architectures implimented

Basic Models

• Linear Regression - Single Variable
• Linear Regression - Multi Variables
• Logistic Regression with gradient descent - binary classification
• Logistic Regression with gradient descent - multi classification
• Simple Neural Network

Model Layers

Activation Functions

General Models

• AlexNet: https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks
• ZFNet: https://arxiv.org/abs/1311.2901
• VGG16: https://arxiv.org/abs/1505.06798
• ResNet: https://arxiv.org/abs/1704.06904
• GoogLeNet: https://arxiv.org/abs/1409.4842
• Inception: https://arxiv.org/abs/1512.00567
• Xception: https://arxiv.org/abs/1610.02357
• MobileNet: https://arxiv.org/abs/1704.04861

Semantic Segmentation

• FCN: https://arxiv.org/abs/1411.4038
• SegNet: https://arxiv.org/abs/1511.00561
• UNet: https://arxiv.org/abs/1505.04597
• PSPNet: https://arxiv.org/abs/1612.01105
• DeepLab: https://arxiv.org/abs/1606.00915
• ICNet: https://arxiv.org/abs/1704.08545
• ENet: https://arxiv.org/abs/1606.02147

Generative adversarial networks

• GAN: https://arxiv.org/abs/1406.2661
• DCGAN: https://arxiv.org/abs/1511.06434
• WGAN: https://arxiv.org/abs/1701.07875
• Pix2Pix: https://arxiv.org/abs/1611.07004
• CycleGAN: https://arxiv.org/abs/1703.10593

Object detection

• RCNN: https://arxiv.org/abs/1311.2524
• Fast-RCNN: https://arxiv.org/abs/1504.08083
• Faster-RCNN: https://arxiv.org/abs/1506.01497
• SSD: https://arxiv.org/abs/1512.02325
• YOLO: https://arxiv.org/abs/1506.02640
• YOLO9000: https://arxiv.org/abs/1612.08242