eliekawerk Goto Github PK

seldon-core-tutorial

seqtestblog-spotify-sequential-testing

Simulation files for Schultzberg & Ankargren blogpost 2023

serve

Model Serving on PyTorch

serverless-machine-learning

Examples of deploying scikit, spaCy and Keras (TensorFlow) machine learning models to AWS Lambda with Serverless framework and Python 3.

serverless-ml-course

Serverless Machine Learning Course for building AI-enabled Prediction Services from models and features

shared-bikes-optimization

Group project aimed at optimizing shared bikes allocation across stations for the city of Chicago

shiny-salesman

Traveling salesman with simulated annealing, R, and Shiny

sigir-2022

This repository contains the 2nd place solution for SIGIR's 2022 Fashion Outfits Challenge hosted by Farfetch.

size-fit-net

PyTorch Implementation of A Deep Learning System for Predicting Size and Fit in Fashion E-Commerce (RecSys'19)

smartphone_sensor_stream

Stream smartphone data with FastAPI, Kafka, QuestDB, and Docker.

software-engineering-for-ai-ml----an-annotated-bibliography

Software Engineering for AI/ML -- An Annotated Bibliography

sparkify_customer_churn

Modeling customer churn with Spark

speech_projects

Speech projects for nascent public speakers

sphere-data-engineering-for-machine-learning

Supporting materials/code examples for my course in data engineering for machine learning.

spotify-recommender-training

Recommendation systems used for Spotify tasks

springboard

Assignments for Springboard's Data Science Career Track program

springboard-1

Here lives all content developed during SpringBoard data engineering bootcamp

springboardaic

Springboard Artificial Intelligence / Machine Learning Career Track

starbucks_promotion_optimization

An exercise based on simulated data from Starbucks to analyze results of an experiment and optimize a promotional strategy based on these results.

startupdatascience

stat479-deep-learning-ss19

Course material for STAT 479: Deep Learning (SS 2019) at University Wisconsin-Madison

stat479-machine-learning-fs19

Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison

stat_rethinking_2023

Statistical Rethinking Course for Jan-Mar 2023

statsforecast

Lightning ⚡️ fast forecasting with statistical and econometric models.

stock-market-crashes

How to detect stock market crashes with topology.

storytelling-with-data

Plots from the book "Storytelling with data" implementation using Python and matplotlib

streaming_nd

Data Streaming Nanodegree (from Udacity) exercises, projects and their solutions

structural_causal_model

structuring_ml_project

sustainable_deepfashion

Imagine you are all about protecting the environment, trying to address some problems of fast fashion, and want to wear sustainable clothing only. You care a lot about fashion, too! But it's hard to find sustainable pieces that match the ideas you have for your look. Imagine you could take a picture of a trendy person on the street and get recommendations on what they are wearing, but from a second-hand market. This is what our app deep fashion does.