Code, IA et Actus Tech : Votre Source d’Inspiration
Explore in-depth articles on programming, analyses of innovative GitHub projects, and guides on advanced Python frameworks and techniques.
The Siamese network learns to compare two inputs by measuring their similarity. Complete guide with contrastive loss, triplet loss, and Keras code.
Siamese Network: Siamese Networks for Similarity Lire
DeepSORT combines object detection and tracking to follow each object in a video. Complete guide with Kalman algorithm and Python code.
DeepSORT: Multi-Object Tracking with Deep Learning Lire
YOLO is the fastest object detection algorithm in the world. Complete guide with architecture, anchor boxes, and Python code.
YOLO: Real-Time Object Detection Lire
The Vision Transformer applies the Transformer architecture to images by cutting them into patches. Complete guide with PyTorch code.
Vision Transformer (ViT): Transformer Applied to Images Lire
Word embeddings represent words as dense vectors capturing semantic meaning. Complete guide with Word2Vec, GloVe, and FastText.
Word Embeddings: Word2Vec, GloVe, FastText Lire
GPT is a generative language model based on the Transformer decoder-only architecture. Complete guide with architecture, pre-training, and Python code.
GPT: Generative Pre-trained Transformer Lire
ResNet introduces residual connections to train very deep networks. Complete guide with Keras code.
ResNet: Residual Network and Skip Connections Lire
BERT is a pre-trained bidirectional language model that revolutionized NLP. Complete guide with fine-tuning and Python code.
BERT: Bidirectional Language Models Lire
The Transformer uses only attention to process sequences. Complete guide with encoder-decoder, positional encoding, and Python code.
Transformer: Transformer Architecture and Self-Attention Lire
The attention mechanism allows neural networks to focus on relevant parts of the input. Complete guide with self-attention and Python code.
Attention Mechanism: Attention Mechanism Lire