yandexdataschoolnlp_course

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Nlp Course

YSDA course in Natural Language Processing

Natural Language Processing - Provides a comprehensive educational curriculum covering NLP from word embeddings to dialogue systems.

Natural Language Processing Resources - Teaches NLP concepts from word embeddings to dialogue systems through structured assignments and lectures.

Homework Assignments - Provides graded homework assignments that apply NLP techniques to real-world problems.

Educational Implementations - Provides hands-on assignments for building and visualizing n-gram and neural language models.

Dialogue Systems - Teaches construction of task-oriented and open-domain conversational agents using retrieval and generative approaches.

Curricula - Teaches natural language processing through a structured course covering foundational embeddings through modern dialogue systems.

Educational Implementations - Provides assignments for training n-gram and neural language models from scratch.

Sequence-to-Sequence Translation Tasks - Teaches building encoder-decoder models with attention mechanisms for translating text between languages.

Seq2Seq Attention Models - Implements encoder-decoder architectures with attention mechanisms for sequence translation.

Conversational Dialogue Systems - Constructs task-oriented and open-domain conversational agents using retrieval and generative approaches.

Word Embeddings - Teaches distributional semantics and vector representations using LSA, Word2Vec, and GloVe.

Neural Machine Translation - Implements encoder-decoder models with attention mechanisms for machine translation tasks.

Part-of-Speech Taggers - Teaches part-of-speech tagging using structured perceptron and dynamic oracles.

Text Classification - Applies convolutional and recurrent networks to categorize text for sentiment or topic prediction.

Text Classifiers - Applies convolutional and recurrent neural networks to categorize text.

Word Alignment Extractions - Learns word alignments between parallel texts using expectation-maximization algorithms.

Dialogue Systems - Constructs task-oriented and open-domain conversational agents using retrieval and generative approaches.

Python Data Science Courses - Teaches NLP using Python with NumPy, PyTorch, and NLTK for all assignments and examples.

Programming Assignments - Provides weekly programming assignments that implement core NLP algorithms from scratch.

Scaffolded Implementations - Guides students through implementing complex algorithms with pre-written stubs and tests.

Weekly Module Progressions - Builds knowledge progressively through weekly modules from embeddings to dialogue systems.

Jupyter Notebook Curricula - Delivers interactive code cells and visualizations in the browser for experimenting with NLP models.

Lecture-Notebook Pairs - Pairs each lecture topic with a Jupyter notebook for immediate hands-on practice.

Blog-Style Lectures - Delivers lecture content as intuitive, engaging blog-style pages that are complete and up-to-date.

NLP Lecture Slides - Provides structured lecture slides covering core natural language processing topics.

Programming Assignments - Provides weekly programming assignments that implement core NLP algorithms from scratch.

Algorithm Scaffolding - Provides pre-written stubs and tests for implementing attention mechanisms and structured perceptrons.

Document Summarization - Produces concise summaries of longer texts using extractive or abstractive methods.

Word Alignment - Learns word alignments between parallel corpora using EM algorithms for translation tasks.

Educational Explanations - Includes dedicated analysis sections in lectures to explain model internals.

Text Summarization - Produces concise summaries by selecting key sentences or generating new text from source documents.

Python NLP Libraries - Teaches NLP algorithms using Python with NumPy, PyTorch, and NLTK for all assignments and examples.

Educational Curricula - Teaches NLP algorithms using Python with NumPy, PyTorch, and NLTK for all assignments and examples.

Domain Adaptation Techniques - Adapts a general machine translation model to a specific domain by matching features and distilling knowledge.

NLP Seminar Exercises - Offers seminar materials with hands-on exercises to reinforce NLP concepts taught in lectures.

Paper Summaries - Summarizes key results and reasoning from top NLP papers for quick understanding.

Summaries - Summarizes key results and reasoning from influential NLP papers.

Research Skill Development - Guides learners to identify flaws, hypothesize improvements, and explore prior work.