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Concept

Word2vec

Related lectures (30)

Neural Networks for NLP Log in to Mediaspace to watch this video

Covers modern Neural Network approaches to NLP, focusing on word embeddings, Neural Networks for NLP tasks, and future Transfer Learning techniques.

Text Models: Word Embeddings and Topic Models Log in to Mediaspace to watch this video

Explores word embeddings, topic models, Word2vec, Bayesian Networks, and inference methods like Gibbs sampling.

Word Embedding Models: Optimization and Applications Log in to Mediaspace to watch this video

Explores optimizing word embedding models, including loss function minimization and gradient descent, and introduces techniques like Fasttext and Byte Pair Encoding.

Optimization in Machine Learning Log in to Mediaspace to watch this video

Explores optimization techniques, word embeddings, and recommendation systems in machine learning.

Natural Language Processing: Understanding Transformers and Tokenization Log in to Mediaspace to watch this video

Provides an overview of Natural Language Processing, focusing on transformers, tokenization, and self-attention mechanisms for effective language analysis and synthesis.

Word Embeddings: Pytorch Basics and Evaluation Log in to Mediaspace to watch this video

Covers Pytorch basics, pre-trained word embeddings, evaluation methods, and practical exercises.

Word Embeddings: Modeling Word Context and Similarity Log in to Mediaspace to watch this video

Covers word embeddings, modeling word context and similarity in a low-dimensional space.

Latent Semantic Indexing Log in to Mediaspace to watch this video

Covers Latent Semantic Indexing, word embeddings, and the skipgram model with negative sampling.

Pre-Training: BiLSTM and Transformer Log in to Mediaspace to watch this video

Delves into pre-training BiLSTM and Transformer models for NLP tasks, showcasing their effectiveness and applications.

Natural Language Processing Log in to Mediaspace to watch this video

Introduces Natural Language Processing, covering text preprocessing, sentiment analysis, and topic analysis, with a focus on building a climate change risk index.