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mrsr

MRSR - Matlab Recommender Systems Research is a software framework for evaluating recommender systems in Matlab.

ms-gsp

MS - GSP (Minimum Support - Generalized Sequential Pattern) Mining Algorithm Implementation

ms-gsp-webmining

This is a recommendation engine developed using Minimum Support GSP ( Generalised Sequential Pattern ) algorithm to find the relationship between items frequently bought together across transactions made by customers. This could also be used to recommend/analyse webpages visited by the user based on their pervious history of webpage visits.

ms_hackathon

mscstatisticsnotes

These are cheat sheets and notes I made as part of an MSc in Statistics, at the University of Sheffield, UK.

msda-denoising

Using a very fast denoising autoencoder

msdchallenge

Million Song Dataset Challenge entry code

msgs

This is a repository for the paper on testing inductive bias with scaled-down RoBERTa models.

msgsp_sequential_pattern_mining

mslearn-dp100

Lab files for Azure Machine Learning exercises

msmarco-bio

A subset of the Popular MSMarco Passage Retrieval Dataset related to Health and Medicine

msps

Mining Sequential patterns using Prefix Span

mstweedie

Multi-source sparse Tweedie modelling

msu

описание тем исследовательских работ для студентов

msu_bna

msu_cpp_autumn_2019

msu_ml1_autumn_2019

msu_python_autumn_2019

msuml

курс "Методы машинного обучения" для 3го потока 3го курса ВМК МГУ

mtcgeohack.112

Public solution for MTC Geohack.112

mtga

Multi-Tasking Genetic Algorithm (MTGA) for multi-task global optimization

mtlsa

A Multi-Task Learning Formulation for Survival Analysis

mtpa

Modeling Techniques in Predictive Analytics with Python and R

mts-geohack

МТС Geohack.112: Соревнование по прогнозированию на гео-данных

mts_kion

data from the MTS Kion application on user interactions with content for a period of 6 months.

mudi-stream

A multi density clustering algorithm for evolving data stream

mulan

multi-agent-ai

In real-time bidding for advertisement, we can take a more data-driven approach to create an optimal bidding strategy. Developed using Python and Jupyter Notebook. Utilises Game Theory for optimal bidding strategy.

multi-agent-distributed-ppo-traffc-light-control

multi agent RL for traffic light control in Sumo using distributed PPO

multi-categorical-gans

Code for the paper "Generating Multi-Categorical Samples with Generative Adversarial Networks"