Topic 1: Introduction and Linguistics 1531


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Languages and Automata Shay Cohen 2017
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Introduction to Natural Language Processing' ETHZ' 2013
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Introduction to Theoretical Computer Science: Introduction Boaz Barak 2021
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Probabilities 2 Dragomir Radev 2018
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Basic Concepts K-nearest neighbors Ansaf Salleb-Aouissi' 2019
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Gaussian Elimination Philip Klein 2013
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Optimization and Neural Nets Pieter Abbeel, Dan Klein 2018
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Pattern Recognition and Machine Learning Chapter 1: Introduction Christopher M. Bishop 2016
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Literary Event Detection Matthew Sim, Jong Ho Park, David Bamman 2019
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Introduction, Vector Space Review Karl Stratos 2018
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What if P equals NP? Boaz Barak 2021
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Context-sensitive languages Shay Cohen 2017
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NLP Tasks 2 Dragomir Radev 2016
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Linear Algebra 2 Dragomir Radev 2018
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Bayes Theorem Dragomir Radev 2017
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Parts of Speech Dragomir Radev 2018
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Stochastic Gradient Descent David McAllester 2017
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Sparse coding Hugo Larochelle 2017
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Computational Systems Biology: Deep Learning in the Life Sciences - Exam Solutions Manolis Kellis 2020
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Exponential Family and Generalized Linear Models Nicholas Zabaras 2017
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Kraft Inequality; Source Coding Theorem; Huffman Coding Frank Keller 2006
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Data-driven Solvers for Inverse Problems He Sun 2020
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Ego Nets Mladen Kolar and Rob McCulloch 2015
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Lecture 5: Morphology' Kai-Wei Chang' 2016
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Introduction to Natural Language Processing Jacob Eisenstein 2014
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Neural Network LMs Mark Yatskar 2021
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Text Corpora Nathan Schneider 2018
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Naive Bayes Lu Wang 2017
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Bayesian Linear Regression John Paisley 2017
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Foundations Moses Charikar and Dorsa Sadigh 2019
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Collaborative Filtering John Paisley 2017
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Gene regulation, chromatin accessibility, DNA regulatory code Manolis Kellis 2020
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History of NLP Dragomir Radev 2018
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Introduction and Class Logistics Dragomir Radev 2017
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Why do we need data? Nathan Schneider 2019
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Introduction and Optimization Problems Eric Grimson, John Guttag, Ana Bel 2016
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Basic Text Processing Regular Expressions Dan Jurafsky 2017
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MIT Probability Course Summarized Zaid Alyafeai 2018
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Optimization: Part II Jorge Nocedal 2018
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Machine Learning for Data Science John Paisley' 2019
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Multiplication of Ax Using Columns of A Gilbert Strang 2019
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Gradient descent François Fleuret 2019
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Discrete Neural Turing Machines Joan Bruna 2016
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Canonical Correlation Analysis Razvan C. Bunescu' 2019
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Midterm Review Alan Ritter 2017
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Expectation and Related Concepts Chebyshevs Theorem Frank Keller 2016
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Functions with Infinite domains, Automata, and Regular expressions Boaz Barak 2021
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Introducing morphology Usama Soltan 2015
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Lecture 7: Word Embeddings' Kai-Wei Chang' 2016
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Continuous Random Variables and Density 2 Frank Keller 2016
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The Function Philip Klein 2013
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Quantitative Methods in Linguistics – Lecture 1 Adrian Brasoveanu 2014
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Introduction Dragomir Radev 2018
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Proofs and algorithms Boaz Barak 2021
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Variational Inference: Loopy Belief Propagation Eric Xing 2014
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A First Look at Structures Dan Roth 2017
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Learning guarantees for infinite hypothesis sets. Mehryar Mohri 2018
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Sample Spaces, Events, Probabilities Frank Keller 2006
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Spectral Algorithms for Graphical Models Eric Xing 2014
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Introduction to NLP Kai-Wei Chang 2017
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Language and thought Usama Soltan 2015
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Natural language processing - preprocessing Hugo Larochelle 2017
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Bayes Rule and Esti