Anchor Text Indexing and Page Ranking

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Related lectures (30)

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Link-based Ranking: Fundamentals and Algorithms

Covers the fundamentals and algorithms of link-based ranking, including anchor text indexing, PageRank, HITS, and practical implementations.

Neural Networks: Training and Activation

Explores neural networks, activation functions, backpropagation, and PyTorch implementation.

Practical Computation of PageRank

Covers the practical computation of PageRank using iterative methods and the challenges of the eigen-vector method.

Link-Based Ranking: PageRank

Explores link-based ranking with a focus on PageRank algorithm and its practical application in web search engines.

Calcul and algorithms: methodology

Explores the PageRank algorithm used by Google to rank web pages.

Creating Links with <A>

Covers the creation of links using the tag in HTML.

Binary Sentiment Classifier Training

Covers the training of a binary sentiment classifier using an RNN.

Document Classification: Transformers and MLPs

Explores transformers and MLPs for document classification, emphasizing their benefits over traditional methods.

Foundations of Deep Learning: Transformer Architecture Overview

Covers the foundational concepts of deep learning and the Transformer architecture, focusing on neural networks, attention mechanisms, and their applications in sequence modeling tasks.

Neural Networks for NLP

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