fjlstar

fjlstar

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fjlstar's repositories

bootcamp

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.

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deep-learning-with-r-notebooks

R notebooks for the code samples of the book "Deep Learning with R"

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experiments

Some research experiments

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gpt_pr

Generate Tweet texts using OpenAI's GPT-3 based Davinci model

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implicit-sgd

Using stochastic gradient descent (SGD) with explicit and implicit updates to fit large-scale statistical models.

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Instacart

2nd place solution🥕🥈

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LDAtools

R package to fit LDA topic models (deprecated)

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leaflet

R Interface to Leaflet Maps

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machinelearningnotes

Notes for the courses in the Machine Learning Specialization created by the University of Washingtion on Coursera

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MetaRec

PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models (IN PROGRESS)

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NVTabular

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

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RecSys2019_DeepLearning_Evaluation

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

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redis-langchain-chatbot

In this tutorial we build a conversational retail shopping assistant that helps customers find items of interest that are buried in a product catalog.

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TalkingDataUserDemographics

In this competition, Kagglers are challenged to build a model predicting users’ demographic characteristics based on their app usage, geolocation, and mobile device properties. Doing so will help millions of developers and brand advertisers around the world pursue data-driven marketing efforts which are relevant to their users and catered to their preferences.

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taskscheduleR

Schedule R scripts/processes with the Windows task scheduler.

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TextRank4ZH

从中文文本中自动提取关键词和摘要

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woe

R Package - calculate Information Value and WoE (Weight of Evidence)

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