[MINI] The Perceptron
Data Skeptic10 Maalis 2017

[MINI] The Perceptron

Today's episode overviews the perceptron algorithm. This rather simple approach is characterized by a few particular features. It updates its weights after seeing every example, rather than as a batch. It uses a step function as an activation function. It's only appropriate for linearly separable data, and it will converge to a solution if the data meets these criteria. Being a fairly simple algorithm, it can run very efficiently. Although we don't discuss it in this episode, multi-layer perceptron networks are what makes this technique most attractive.

Tämä jakso on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi jakso saattaa sisältää mainontaa.

Jaksot(601)

Video Recommendations in Industry

Video Recommendations in Industry

In this episode, Kyle Polich sits down with Cory Zechmann, a content curator working in streaming television with 16 years of experience running the music blog "Silence Nogood." They explore the inter...

26 Joulu 202538min

Eye Tracking in Recommender Systems

Eye Tracking in Recommender Systems

In this episode, Santiago de Leon takes us deep into the world of eye tracking and its revolutionary applications in recommender systems. As a researcher at the Kempelin Institute and Brno University,...

18 Joulu 202552min

Cracking the Cold Start Problem

Cracking the Cold Start Problem

In this episode of Data Skeptic, we dive deep into the technical foundations of building modern recommender systems. Unlike traditional machine learning classification problems where you can simply ap...

8 Joulu 202539min

Designing Recommender Systems for Digital Humanities

Designing Recommender Systems for Digital Humanities

In this episode of Data Skeptic, we explore the fascinating intersection of recommender systems and digital humanities with guest Florian Atzenhofer-Baumgartner, a PhD student at Graz University of Te...

23 Marras 202536min

DataRec Library for Reproducible in Recommend Systems

DataRec Library for Reproducible in Recommend Systems

In this episode of Data Skeptic's Recommender Systems series, host Kyle Polich explores DataRec, a new Python library designed to bring reproducibility and standardization to recommender systems resea...

13 Marras 202532min

Shilling Attacks on Recommender Systems

Shilling Attacks on Recommender Systems

In this episode of Data Skeptic's Recommender Systems series, Kyle sits down with Aditya Chichani, a senior machine learning engineer at Walmart, to explore the darker side of recommendation algorithm...

5 Marras 202534min

Music Playlist Recommendations

Music Playlist Recommendations

In this episode, Rebecca Salganik, a PhD student at the University of Rochester with a background in vocal performance and composition, discusses her research on fairness in music recommendation syste...

29 Loka 202552min

Bypassing the Popularity Bias

Bypassing the Popularity Bias

15 Loka 202534min

Suosittua kategoriassa Tiede

rss-mita-tulisi-tietaa
rss-poliisin-mieli
tiedekulma-podcast
menologeja-tutkimusmatka-vaihdevuosiin
sotataidon-ytimessa
filocast-filosofian-perusteet
rss-duodecim-lehti
rss-astetta-parempi-elama-podcast
rss-lapsuuden-rakentajat-podcast
utelias-mieli
docemilia
radio-antro
rss-ranskaa-raakana
rss-kasvatuspsykologiaa-kaikille
rss-tiedetta-vai-tarinaa
rss-luontopodi-samuel-glassar-tutkii-luonnon-ihmeita
rss-sosiopodi