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Edward Elson Kosasih
Edward Elson Kosasih

116 Followers

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Published in

Towards Data Science

·Pinned

One Class Learning in Manufacturing: Autoencoder and Golden Units Baselining

Recently I’ve been working with manufacturing customers (both OEM and CM) who want to jump on the bandwagon of machine learning. One common use case is to better detect products (or Device Under Test/DUT) that are defective in their production line. Using machine learning’s terminology, this falls under the problem…

Machine Learning

10 min read

One Class Learning in Manufacturing: Autoencoder and Golden Units Baselining
One Class Learning in Manufacturing: Autoencoder and Golden Units Baselining
Machine Learning

10 min read


Dec 29, 2021

Multivariate Time Series Analysis Template

If you’re looking for a standard boilerplate to analyse multivariate time-series data, this is for you! — In this post, I present standard steps that can be used for multivariate time series analysis, including application in forecasting. There are six steps that we will perform: 1. Causality Test 2. Cointegration Test 3. Stationarity Test and Make Stationary 4. Find optimal order p for VAR(p) 5. Residual Serial Correlation Test 6. Forecast and…

5 min read

Multivariate Time Series Analysis Template
Multivariate Time Series Analysis Template

5 min read


Dec 28, 2021

Univariate Time Series Analysis Template

If you’re looking for a standard boilerplate to analyse univariate time-series data, this is for you! — In this post, I present standard steps that can be used for time series analysis, including application in forecasting. There are three steps that we will perform: 1. Check for Stationarity. Use 3 tests: ADF, KPSS and autocorrelation. 2. If signal is non-stationary, make it stationary. Use either transformation: Detrending, Differencing…

2 min read

Univariate Time Series Analysis Template
Univariate Time Series Analysis Template

2 min read


Published in

Towards Data Science

·Jan 17, 2021

Link Prediction and Information Theory: A Tutorial

Using Mutual Information to measure the likelihood of candidate links in a graph. — During my literature review, I stumbled upon an information-theoretic framework to analyse the link prediction problem (Tan et al. (2014), Kumar and Sharma (2020)). For an overview of what link prediction is, read my previous article here. The basic idea is to predict unseen edges in a graph. Such edges…

Network Science

5 min read

Link Prediction and Information Theory: A Tutorial
Link Prediction and Information Theory: A Tutorial
Network Science

5 min read


Published in

Towards Data Science

·Nov 23, 2020

Link Prediction in Bipartite Graph

What’s the one common thing between finding colleagues in Linkedin, friends in Facebook, co-authors in Google Scholar, dates in Tinder, products recommendation in Amazon, new songs in Spotify, movies advice in Netflix, new suppliers in supply chain and interactions of gene/protein in a biological network? — Answer: They can all be mathematically formulated as a graph link prediction problem! In short, given a graph G (V, E) with |V| vertices and |E| edges, our task is to predict the existence of a previously unknown edge e_12 ∉ E between vertices v_1, v_2 ∈ V. We can…

Data Science

11 min read

Link Prediction in Bipartite Graph
Link Prediction in Bipartite Graph
Data Science

11 min read


Published in

Towards Data Science

·Oct 12, 2020

Simple Deployment of a Graph Database: JanusGraph

I’ve recently been looking for an open-source, distributed graph database, as I need to store a large graph data somewhere persistently. My main requirement is that I’d like to have as much control as possible over the underlying storage and indexing system behind such aforementioned database. I stumbled upon JanusGraph…

Graph Database

5 min read

Simple Deployment of a Graph Database: JanusGraph
Simple Deployment of a Graph Database: JanusGraph
Graph Database

5 min read


Published in

Towards Data Science

·Jun 22, 2020

Geometric Deep Learning: A Quick Tour

The following document provides a whirlwind tour of some fundamental concepts in geometric deep learning. — Find the latex-written version of this article here The following document provides a whirlwind tour of some fundamental concepts in geometric deep learning. The mathematical derivations might not be as rigorously shown and some equations are stated without proofs. This is done intentionally to keep the document short yet comprehensive…

Geometric Deep Learning

5 min read

Geometric Deep Learning: A Quick Tour
Geometric Deep Learning: A Quick Tour
Geometric Deep Learning

5 min read


Published in

Cambridge University Technology and Enterprise Club

·May 12, 2020

Keeping in Touch

This year marks the 17th anniversary of CUTEC. So I thought I’ll reach out to our former committees to see how they are doing and perhaps ask for a few thoughts on how the CUTEC experience, in hindsight, contributes to their life. The responses are surprisingly very encouraging! Do take…

Alumni

7 min read

Keeping in Touch
Keeping in Touch
Alumni

7 min read


Published in

Analytics Vidhya

·Feb 2, 2020

Interpreting Posterior of Gaussian Process for Regression

I recently learned about Gaussian Process (GP) and how it can be used for regression. However, I have to admit that I had a hard time grasping the concept. It was only after I derived the equations and tried going through a few samples did I manage to start deciphering…

Gaussian Process

5 min read

Interpreting Posterior of Gaussian Process for Regression
Interpreting Posterior of Gaussian Process for Regression
Gaussian Process

5 min read


Published in

Towards Data Science

·Feb 1, 2020

Servitization and Queueing Theory: Deriving M/M/1 Model

Servitization is a phenomena where manufacturing firms shift from selling pure products to offering solutions (services) instead. Neely (2013) provides a brief introduction on how companies across industries are adopting this business model. What’s interesting is that servitization also results in a less clear boundary between manufacturing and service firms…

Operations Research

7 min read

Servitization and Queueing Theory: Deriving M/M/1 Model
Servitization and Queueing Theory: Deriving M/M/1 Model
Operations Research

7 min read

Edward Elson Kosasih

Edward Elson Kosasih

116 Followers

Machine Learning | Network Science | Supply Chain and Manufacturing Analytics | eekosasih.com

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