Remove 2013 Remove Deep Learning Remove Metrics Remove Predictive Modeling
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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model.

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Why you should care about debugging machine learning models

O'Reilly on Data

More structured approaches to sensitivity analysis include: Adversarial example searches : this entails systematically searching for rows of data that evoke strange or striking responses from an ML model. Figure 1 illustrates an example adversarial search for an example credit default ML model. 2] The Security of Machine Learning. [3]

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Credit Card Fraud Detection using XGBoost, SMOTE, and threshold moving

Domino Data Lab

deep learning) there is no guaranteed explainability. We will go through a typical ML pipeline, where we do data ingestion, exploratory data analysis, feature engineering, model training and evaluation. from sklearn import metrics. from sklearn import metrics. The only intact features are Time and Amount.