Lectures related to Text Handling: Matrix, Documents, Topics

Text Data Processing: Basics & Techniques

Introduces the basics of text data processing, covering document retrieval, classification, sentiment analysis, and topic detection.

Linear Systems: Diagonal and Triangular Matrices, LU Factorization

Covers linear systems, diagonal and triangular matrices, and LU factorization.

Text Data Analysis: Techniques and Applications

Explores handling text data, deriving clean datasets from unstructured text, and various text analysis techniques.

SVD: Singular Value Decomposition

Covers the concept of Singular Value Decomposition (SVD) for compressing information in matrices and images.

Matrix Operations: LU Factorization & Subspace Vector

Covers LU factorization, determinants, subspaces, and matrix products.

Matrix Inversion

Explores matrix inversion, conditions for invertibility, uniqueness of the inverse, and elementary matrices for inversion.

Matrix Equivalence Theorems

Explores matrix equivalence theorems for systems of equations and least squares solutions.

Deep Learning for NLP

Delves into Deep Learning for Natural Language Processing, exploring Neural Word Embeddings, Recurrent Neural Networks, and Attentive Neural Modeling with Transformers.