Rayan Yassminh – Medium

Rayan Yassminh

Pinned

Rayan Yassminh

Uncovering the Optimal Number of Clusters: Part 1 “Introduction & Background”

Clustering is a method that involves dividing data points into groups, referred to as clusters. Each cluster contains similar data points…

Feb 12, 2023

Uncovering the Optimal Number of Clusters: Part 1 “Introduction & Background”

Feb 12, 2023

Pinned

Rayan Yassminh

Clustering Time Series : Analysis of Housing Prices in Bexar County, TX from 1996 to 2020

Clustering time series is a powerful technique utilized to group similar time series data based on their underlying patterns and…

May 5, 2023

Clustering Time Series : Analysis of Housing Prices in Bexar County, TX from 1996 to 2020

May 5, 2023

Pinned

Rayan Yassminh

What Are the Differences between Accuracy and Precision?

While Wyatt Earp’s quote “Fast is fine, but accuracy is everything” emphasizes the significance of accuracy, it is worth noting that…

Jun 13, 2023

What Are the Differences between Accuracy and Precision?

Jun 13, 2023

Pinned

Rayan Yassminh

Machine Learning Models with AWS SageMaker: Step 1, Pre-processing.

Recently, I have been learning computing in AWS and from my learning journey I will share some of my notes and examples with you. In…

Jan 22, 2023

Machine Learning Models with AWS SageMaker: Step 1, Pre-processing.

Jan 22, 2023

Pinned

Rayan Yassminh

When do we need to one-hot encode?

Probably through your journey in learning data science, you have learned that all independent classes in categorical features should be…

Dec 28, 2022

When do we need to one-hot encode?

Dec 28, 2022

Rayan Yassminh

Master Gradient Descent and Brew the Perfect Cup of Coffee.

Jul 30

Master Gradient Descent and Brew the Perfect Cup of Coffee.

Jul 30

Rayan Yassminh

Practical Applications of Information Theory in Machine Learning

The landscape of data tools is ever-changing. Each day, new libraries and tools are introduced, but they all rely on fundamental…

Jul 8

Practical Applications of Information Theory in Machine Learning

Jul 8

Rayan Yassminh

Practical Bayesian Inference for Data Scientists

Bayesian Inference is a handy statistical method that helps data scientists update the likelihood of a hypothesis as new data or…

Jul 4

Practical Bayesian Inference for Data Scientists

Jul 4

Rayan Yassminh

Transforming City Services with ML: In-Depth Analysis of San Antonio’s 311 System — Part I…

Today’s story resonates with cities worldwide. It is a tale of connection and community. Whether it’s my city or yours, what truly matters…

Jun 7

Transforming City Services with ML: In-Depth Analysis of San Antonio’s 311 System — Part I…

Jun 7

Rayan Yassminh

Business Driving Success: The Dual Impact of Recommendation Systems on User Satisfaction and…

Recommendation systems create a win-win scenario for both customers and businesses. Customers benefit from personalized and relevant…

Apr 6

Business Driving Success: The Dual Impact of Recommendation Systems on User Satisfaction and…

Apr 6

Rayan Yassminh

Rayan Yassminh

I am a machine learning scientist with a broad STEM background. I aim to explain basic concepts using practical and straightforward examples.

Following

Help
Status
About
Careers
Press
Blog
Privacy
Terms
Text to speech
Teams