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032 Cartesian Similarity Metrics

032 Cartesian Similarity Metrics

L1/L2 norm, Manhattan, Euclidean, cosine distances, dot product
Tijd: 42:28
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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)
Aflevering-ID: 1000497618024
GUID: 7f335339-1e45-4ab1-99de-20a9bda41fca
Releasedatum: 8-11-2020 06:10:52

Beschrijving

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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https://machinelearningguide.libsyn.com/rss

Recensies van klanten

Fantastic series. Excellent and clear explanation. Also for non tech

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Navah Hochstein
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2019-10-17
Fascinating course and podcast series.
Explaining it all in a very clear way. Especially for people that are not computer programmers - they can also understand the material in a very good way.
Thank you so much for making the series

Really good pace

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Lmgweb
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2019-09-24
This is the first source I use for machine learning and so far the pace is very inspiring and stimulating. Please continue. Finished episode 4 now.

Great machine learning podcasts

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Mike Breda
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2019-03-15
I am a master AI student. This podcats are great, finally I can really undertand some parts of my studies better. The top-down approach in the podcast is fantastic.

Your Teaching Style

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pariai
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2018-09-12
You’re such a great teacher! Thanks for making these!:)