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Articles by Idit Cohen
The best educators never stop being students | Commentary
Getting your Trinity Audio player ready... For 25 years, I have taught Judaic Studies at David Posnack Jewish Day School in Davie. As a lead educator in Israel Studies, I teach the history of the Jewish people and their enduring connection to the land of Israel.
How to Stand Out as a Junior Data Scientist
7 things you can do to show your skills even if you have no experience at all Every junior scientist feels frustrated when looking for their first job and has nothing to show for it. This post will suggest 7 ways to demonstrate your knowledge of data science before your first interview. At first, joining open-source projects seems to be a daunting task, but it is not necessarily the case.
Assumptions of multiple linear regression
Idit Cohen · Follow 4 min read · -- Building Reliable Models: Understanding and Verifying the Assumptions Behind Multiple Linear Regression Photo by Niklas Jeromin. Sager by Pixabay Generally speaking, many data science practitioners use statistical and machine learning models, without giving much thought to the assumptions behind the constructs.
Explainable AI (XAI) with SHAP -Multi-class classification problem
Image by Pixabay Sager from Pixabay Model explainability becomes a basic part of the machine learning pipeline. Keeping a machine learning model as a “black box” is not an option anymore. Luckily there are analytical tools such as (lime, ExplainerDashboard, Shapash, Dalex and more) that are evolving rapidly and becoming more popular. In a previous post we explained how to use SHAP for a regression problem.
Explainable AI (XAI) with SHAP - regression problem
Image by Startup Stock Photos Sager from Pixabay Model explainability becomes a basic part of the machine learning pipeline. Keeping a machine learning model as a “black box” is not an option anymore. Luckily there are tools that are evolving rapidly and becoming more popular. This guide is a practical guide for XAI analysis of SHAP open source Python package for a regression problem.
Explainable AI (XAI) with a Decision Tree
Image by Jplenio Sager from Pixabay AI, Learning models become more and more complex over time and it becomes difficult to analyze them intuitively. It is often heard that machine learning models are “black boxes”, in the sense that they can make good predictions but we can’t understand the logic behind those predictions. This statement is true in the sense that most data scientists find it difficult to extract insights from models.
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