Introduction
Basics
Optimization
How to prevent overfitting
Linear Algebra
Clustering
Calculate Parameters in CNN
Weight norm and layer norm
Confidence Interval
Quantization
Classical Machine Learning
Neural Networks
Different Types of Convolution
Loss
Hinge Loss
Cross-Entropy Loss
Binary Cross-Entropy Loss
Categorical Cross-Entropy Loss
Optional: Focal Loss
Optional: CORAL Loss
Resnet
Mobilenet
Computer Vision
Two Stage Object Detection
Metrics
ROI
R-CNN
Fast RCNN
Faster RCNN
Mask RCNN
One Stage Object Detection
YOLO
Single Shot MultiBox Detector(SSD)
FPN
Segmentation
Panoptic Segmentation
PSPNet
FaceNet
GAN
Imbalance problem in object detection
NLP
Embedding
RNN
LSTM
Parallel Computeing
Communication
MapReduce
Parameter Server
Decentralized And Ring All Reduce
Federated Learning
Anomaly Detection
DBSCAN
Autoencoder
Visualization
Saliency Maps
Fooling images
Class Visualization
Published with GitBook
Communication
Slides
Youtube
Two ways of communication
Client-Server Architecture
Peer-to-peer architecture
