Multi-Task Learning: Multi-Task Learning
Multi-Task Learning trains a single model on several tasks simultaneously to improve generalization. Complete guide with Python code.
Multi-Task Learning: Multi-Task Learning LireLearn Python
Explore in-depth articles on programming, analyses of innovative GitHub projects, and guides on advanced Python frameworks and techniques.
Semi-Supervised GCN: Graph Classification with Few Labels
GCNs classify nodes on a graph by propagating information from a few labeled nodes to the entire graph. Complete guide with PyTorch Geometric.
Semi-Supervised GCN: Graph Classification with Few Labels Lire
Hyperband: Efficient Hyperparameter Optimization
Hyperband dynamically allocates resources to the best configurations to optimize hyperparameters. Complete guide with Python code.
Hyperband: Efficient Hyperparameter Optimization Lire
Self-Organizing Maps: Kohonen Maps and Topology
Self-Organizing Maps project multidimensional data onto a 2D grid while preserving topology. Complete guide with Python code.
Self-Organizing Maps: Kohonen Maps and Topology Lire
Neural Turing Machine: Differentiable External Memory
Neural Turing Machines combine a neural controller and a differentiable external memory. Complete guide with PyTorch code.
Neural Turing Machine: Differentiable External Memory Lire
Knowledge Distillation: Knowledge Distillation
Knowledge Distillation transfers knowledge from a large model to a small one via soft labels. Complete guide with temperature and Python code.
Knowledge Distillation: Knowledge Distillation Lire
Graph Attention Network (GAT): Attention on Graphs
GAT applies attention to graphs to weight the importance of each neighbor. Complete guide with multi-head attention and PyTorch Geometric code.
Graph Attention Network (GAT): Attention on Graphs Lire
Neural Style Transfer: Artistic Style Transfer
Neural Style Transfer applies the style of one image to the content of another via a pre-trained neural network. Complete guide with PyTorch code.
Neural Style Transfer: Artistic Style Transfer Lire
Anomaly Detection with Autoencoders: Complete Guide
Autoencoders detect anomalies by learning to reconstruct normal data and measuring reconstruction error. Complete guide with PyTorch.
Anomaly Detection with Autoencoders: Complete Guide Lire
Prophet: Time Series Forecasting with Facebook Prophet
Prophet models time series with an additive approach robust to missing data. Complete guide with Python code.
Prophet: Time Series Forecasting with Facebook Prophet Lire