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INTERPRETABLE MACHINE LEARNING: A GUIDE FOR MAKING BLACKBOX MODELS EXPLAINABLE

By:

MOLNAR, CHRISTOPH

Publication details: SHROFF PUBLISHERS & DISTRIBUTORS, NAVI MUMBAI 2024Edition: 2ISBN:

9789355428370

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Holdings
Item type	Current library	Collection	Call number	Status	Notes	Date due	Barcode
Reference	Modern College of Arts, Science and Commerce (Autonomous), Shivajinagar, Pune-5 On Display	Reference	006.3/MOL (Browse shelf(Opens below))	Not for loan	Computer Science		NG5857

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Previous	006.3/KAA DEEP LEARNING FOR FINANCE: CREATING MACHINE AND DEEP LEARNING MODELS FOR TRADING IN PYTHON	006.3/KAN PROBABILISTIC MACHINE LEARNING FOR FINANCE AND INVESTING: A PRIMER TO GENERATIVE AI WITH PYTHON	006.3/LEE GRAPH-POWERED ANALYTICS AND MACHINE LEARNING WITH TIGERGRAPH: DRIVING BUSINESS OUTCOMES WITH CONNECTED DATA	006.3/MOL INTERPRETABLE MACHINE LEARNING: A GUIDE FOR MAKING BLACKBOX MODELS EXPLAINABLE	006.3/NEL SOFTWARE ENGINEERING FOR DATA SCIENTISTS : FROM NOTEBOOKS TO SCALABLE SYSTEMS	006.3/PAT LEAN AI: HOW INNOVATIVE START-UPS USE ARTIFICIAL INTELLIGENCE TO GROW	006.3/PET FUNDAMENTALS OF DATA OBSERVABILITY: IMPLEMENT TRUSTWORTHY END TO END DATA SOLUTIONS	Next

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