Interpretable Machine Learning with Serg Masis

Serg Masis is the author of best-selling book 'Interpretable Machine Learning with Python' and senior Data Scientist at Sygenta. He has mentored many data scientists around the world.  Timestamps: 00:00 intro 08:30  Old 4.77 MH  z Computer, Late 80s and Programming 11:51 Fairness, Accountability and Transparency in Machine Learning, Startup and Harvard 16:33  Fairness vs Preciseness, Bias and Variance Tradeoff, Are Engineers to blame? 21:43 Mask-Detection Problem in Coded-Bias, Biased Samples,  Surveillance using CV 32:38 Fixing Biased Datasets, Augmenting Data and Limitations  37:39 Algorithmic Optimisation and Explainability 40:51 Eric Schmidt on Behavioral Prediction, SHAP values, Tree and DeepExplainers 44:50 Challenges of using SHAP and LIME & Big Data 49:37 GPT3, Large Models and ROI on Explainability 01:00:00  TCAS, Collision Risks and Interpretability, Ransom Attacks 01:08:09 Guitar, Bass, and Led Zepplin 01:09:31 Birth Order and IQ, Science vs Folk Wisdom 01:13:30  Reverse Discrimination & Men, Bias in Child Custody, Prison Sentences, and Incarceration 01:23:11 Receidivism to Criminal Behaviour, Ethnic over-representation & Systematic Racism 01:24:44  Human Judges vs AI,  Absolute Fairness, Food and Parole 01:30:20  Face Detection in China, Privacy vs Convenience, Feature Engineering and Model Parsimony  01:35:51 Sparsity, Interaction Effects, and Multicollinearity 01:38:23  Four levels of Global and Local Predictive Explainability 01:43:17  Recursive and Sequential Feature Selection 01:47:42  Ensemble, Blended and Stacked Models and Interpretability 01:53:45  In-Processing and Post-Processing Bias Mitigation 01:57:00  Future of Interpretable AI --- Send in a voice message: https://podcasters.spotify.com/pod/show/minhaaj/message

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Minhaaj Podcast are Candid Conversations with Some of the Most Intelligent People. From Forbes and WSJ contributors, inventors, wall street bankers, Fintech experts, memory champions, neuroscientists, psychology veterans, FAANG employees and Youtube Educators, i have had the distinct pleasure to learn from these luminaries, for which i shall remain thankful, forever.