Tag

data

Clustering Data into Groups, Part 3

From Data Science Bookcamp by Leonard Apeltsin

This 3-part article series covers:

Clustering data by centrality
Clustering data by density
Trade-offs between clustering algorithms
Executing clustering using the scikit-learn library
Iterating over clusters using Pandas

Clustering Data into Groups, Part 2

From Data Science Bookcamp by Leonard Apeltsin

This 3-part article series covers:

Clustering data by centrality
Clustering data by density
Trade-offs between clustering algorithms
Executing clustering using the scikit-learn library
Iterating over clusters using Pandas

Clustering Data into Groups, Part 1

From Data Science Bookcamp by Leonard Apeltsin

This 3-part article series covers:

Clustering data by centrality
Clustering data by density
Trade-offs between clustering algorithms
Executing clustering using the scikit-learn library
Iterating over clusters using Pandas

Bias and Fairness in Machine Learning, Part 3: building a bias-aware model

From Feature Engineering Bookcamp by Sinan Ozdemir

This article series covers

●      Recognizing and mitigating bias in our data and model

●      Quantifying fairness through various metrics

●      Applying feature engineering techniques to remove bias from our model without sacrificing model performance

Bias and Fairness in Machine Learning, Part 2: building a baseline model and features

From Feature Engineering Bookcamp by Sinan Ozdemir

This article series covers

●      Recognizing and mitigating bias in our data and model

●      Quantifying fairness through various metrics

●      Applying feature engineering techniques to remove bias from our model without sacrificing model performance

Bias and Fairness in Machine Learning, Part 1: introducing our dataset and the problem

From Feature Engineering Bookcamp by Sinan Ozdemir

This article series covers

●   Recognizing and mitigating bias in our data and model

●   Quantifying fairness through various metrics

●   Applying feature engineering techniques to remove bias from our model without sacrificing model performance

Data Inventory: what it is and why you need it 

From Privacy Engineering by Nishant Bhajaria

The term “Data Inventory” is ill-defined and this article aims to create a definition which is intuitive and actionable.

Ask Dr. Chong: become a leader in data science part 1

In case you missed it, here is Jike Chong and Yue Cathy Chang’s live Twitch coding stream recap. For more, check out the book: How to Lead in Data Science. For more live coding streams, subscribe to Manning’s Twitch channel… Continue Reading →

Identifying Privacy Risks through Asset Management, Governance, and Risk Management

In order to identify privacy risks, you will want to look at your infrastructure and systems as individual units as well as how they interact collectively. Just as engineers need to perform unit testing and integration testing prior to code deployment, privacy engineers need to look at the entire business through a similar inside-out lens.

Automating Privacy by Design, Part 5

From Privacy Engineering by Nishant Bhajaria

This article series explores incorporating privacy into your design from the beginning using automation.

© 2022 Manning — Design Credits