Titlebook: Responsible AI; Implementing Ethical Sray Agarwal,Shashin Mishra Book 2021 The Editor(s) (if applicable) and The Author(s), under exclusive

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書目名稱Responsible AI影響因子(影響力)




書目名稱Responsible AI影響因子(影響力)學(xué)科排名




書目名稱Responsible AI網(wǎng)絡(luò)公開度




書目名稱Responsible AI網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Responsible AI被引頻次




書目名稱Responsible AI被引頻次學(xué)科排名




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書目名稱Responsible AI讀者反饋學(xué)科排名

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Remove Bias from ML Model, be used with most of the machine learning algorithms. These techniques offer a lot of scope for optimization and the business analysts in the team will have to take the lead in understanding and deciding the best approach for the optimization that can be achieved.

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Remove Bias from ML Output,hting) or by adding a step in the modelling process by calculating the residuals (which requires additional model training). Both of these techniques come in when you still haven’t trained your model and allow you to build a model that is fair from grounds up. However, these techniques do not help u

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Data and Model Privacy,sensitive parameters in the data but also help reduce the bias. This chapter explains why you should be considering data and model privacy as an integral part of your responsible AI journey and how you can apply it for the problem you are working on.

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that refer to existing packages. For the techniques covered,.This book is written for software product teams that use AI to add intelligent models to their products or are planning to use it. As AI adoption grows, it is becoming important that all AI driven products can demonstrate they are not intr

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