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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade. See Ribeiro et al.

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Smarten Augmented Analytics Receives CERT-IN Certification for Its Products and Services!

Smarten

” The Information Technology Amendment Act of 2009 designated CERT-IN as the national agency to perform functions for cyber security, including the collection, analysis and dissemination of information on cyber incidents, as well as taking emergency measures to handle incidents and coordinating cyber incident response activities.

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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

To do so, the company started by defining the goals, and finding a way to translate employees’ behavior and experience into data, so as to model against actual outcomes. They used the data collected to build a logistic-regression and unsupervised learning models, so as to determine the potential relationship between drivers and outcomes.

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Exploring US Real Estate Values with Python

Domino Data Lab

Models are at the heart of data science. Data exploration is vital to model development and is particularly important at the start of any data science project. the mouse is hovering over December 2009, and it shows a point near the bottom of the last housing crash, with the median housing price in Palo Alto at $1.2 Introduction.

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The future of casino marketing strategy is digital plus data

BizAcuity

From 2009 to 2019, in a span of 10 years, the United States tripled its gross gaming revenue from $34.3 There is a need for a predictive analytics tool that can individually target each customer at right time to drive additional revenue. On analyzing long-term data, the model suggests optimized options for every dimension.

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

Domino Data Lab

We’ll use a gradient boosting technique via XGBoost to create a model and I’ll walk you through steps you can take to avoid overfitting and build a model that is fit for purpose and ready for production. This is generally problematic, as the model trained on such data will have difficulties recognising the minority class.

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Data Science at The New York Times

Domino Data Lab

Assessing whether a business stakeholder is trying to solve for a problem that is descriptive, predictive, or prescriptive and then re-framing the problem as supervised learning, unsupervised learning, or reinforcement learning, respectively. When he retired in 2009 he had some time on his hands. or a prescriptive model?