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Claire Lee's Projects

arxives icon arxives

arXivES - Search arXiv quickly with Elasticsearch

aws-doc-sdk-examples icon aws-doc-sdk-examples

Welcome to the AWS Code Examples Repository. This repo contains code examples used in the AWS documentation, AWS SDK Developer Guides, and more. For more information, see the Readme.rst file below.

cs515_w21_algo icon cs515_w21_algo

Algorithms + Data Structures implementation & key concepts (e.g., Recursion, DP, Greedy Algo, Randomization, Treaps, Hashing, Network Flow, Linear Programming, and Approximation)

cs519_applied_ml icon cs519_applied_ml

Applied Machine Learning workspace & key concepts covering the basics, linear algebra + numpy, knn, linear classification, linear/nonlinear regression, price prediction, and sentiment analysis

cs539_w21_nlp icon cs539_w21_nlp

Natural Language Processing with Deep Learning Concepts (e.g., Vector Semantics, RNN, Generative Model) & Implementation using PyTorch

cs540_w21_dbms icon cs540_w21_dbms

DBMS workspace & concepts (e.g., Relational Model/Languages, Data Constraints, File Structures/Indexing, Query Processing/Optimization, Concurrency Control, Failure Recovery, Learning over Relational Data)

cs549_scalable_ml icon cs549_scalable_ml

Scalable querying & ML workspace focused on Scalable Algorithms/Data Structures, Learning Over Graphs, Relational Data, Data Augmentation/Preparation

cs561_f20_swe icon cs561_f20_swe

CS 561 Software Engineering Methods - Stock Portfolio Management App Codebase

datasets icon datasets

🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

programming_languages_idris icon programming_languages_idris

Idris code & key concepts in PL (e.g., Curry-Howard isomorphism, Operational Semantics and Type Systems defined by inference rules)

the-pile icon the-pile

Datasets for training models + building DBs

warren icon warren

A flask app to predict stock prices in real time using Facebook's Prophet time series algorithm with a multi-variate, single-step time series forecasting strategy.

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