Faisal Nazir, AWS on "The importance of explainability in AI"

Conference TFNetworkAutumn21

Data Science - The beating heart of AI
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Faisal Nazir has over 22 year’s experience in engineering, development, integration and strategy consulting. In the past Faisal has worked for Motorola, Cisco, Redhat, Booz Allen and now AWS. Faisal has a Masters in Quantum Physics from Imperial College London.

Faisal is currently working as a Machine Learning Specialist for Amazon also has interests in Blockchain Technologies and Quantum Computing and actively works on projects in all three disciplines.

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The importance of explainability in AI

Data scientist could potentially wield great power over the lives of everyday people. This power comes from how they develop ML models that can be used to make life-changing decisions. Explainability - having knowledge of why an model makes an inference - is the field that tries make sense of a models decision. We will discuss what tooling is available to Data Scientists to help them find out what is going on with the models they train.