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Machine Learning Guide

Machine Learning Guide

Släppt: 2020-11-08
© OCDevel copyright 2020
Machine Learning Guide - QR Code
30 avsnitt
Ljud
Lyssna på Apple Podcasts
30 avsnitt
Ljud
Lyssna på Apple Podcasts
Släppt: 2020-11-08
© OCDevel copyright 2020
-42
Senaste avsnittet
032 Cartesian Similarity Metrics

032 Cartesian Similarity Metrics

L1/L2 norm, Manhattan, Euclidean, cosine distances, dot product
Tid: 42:28
Social media Gnothi and email me a screenshot/link for 3-month access to Machine Learning Applied; commit code to the Github repository for life-access.
Normed distances link
A norm is a function that assigns a strictly positive length to each vector in a vector space. link Minkowski is generalized. p_root(sum(xi-yi)^p). "p" = ? (1, 2, ..) for below. L1: Manhattan/city-block/taxicab. abs(x2-x1)+abs(y2-y1). Grid-like distance (triangle legs). Preferred for high-dim space. L2: Euclidean. sqrt((x2-x1)^2+(y2-y1)^2. sqrt(dot-product). Straight-line distance; min distance (Pythagorean triangle edge) Others: Mahalanobis, Chebyshev (p=inf), etc Dot product
A type of inner product.
Outer-product: lies outside the involved planes. Inner-product: dot product lies inside the planes/axes involved link. Dot product: inner product on a finite dimensional Euclidean space link Cosine (normalized dot)
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Utgivningsdatum: 2020-11-08 06:10:52

Beskrivning

Machine learning audio course, teaching the fundamentals of machine learning and artificial intelligence. It covers intuition, models (shallow and deep), math, languages, frameworks, etc. Where your other ML resources provide the trees, I provide the forest. Consider MLG your syllabus, with highly-curated resources for each episode's details at ocdevel.com. Audio is a great supplement during exercise, commute, chores, etc.

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