Events

ElevenPaths Talks Code for Devs

 

Using Machine Learning to Detect Anomalies Web Traffic by Carmen Torrano

December 13, 2017. One of our hacker womens, Carmen Torrano, think about a practical case based on the analysis of algorithms applied to Machine Learning. Are you going to miss this webinar? Connect to the talk!


#CodeTalks4Devs: Using Machine Learning to Detect Anomalies Web Traffic

SDK Go for Latch
SDK Go for Latch Fran Ramírez and Rafael Troncoso (special guest) September 27th
Implementing Data Exfiltration With Latch’sApp
Implementing Data Exfiltration With Latch’sApp Álvaro Núñez-Romero and Pablo González October 18th
DirtyTooth: It’s Only Rock’n’Roll, but I like It
DirtyTooth: Installation in your Raspberry With a DEB Package Álvaro Núñez-Romero and Pablo González November 1st
Latch Cloud TOTP en NodeJS y .NET
Latch Cloud TOTP in NodeJS and .NET Carlos del Prado and Ioseba Palop November 15th
MicroLatch: Building Latch in the Palm of Your Hand
MicroLatch: Building Latch in the Palm of Your Hand Álvaro Núñez-Romero November 29th
.Net Latch integration
.Net Latch integration Ioseba Palop February 21st
JAVA Latch integration
JAVA Latch integration Javier Espinosa Februay 28th
PHP Latch integration
PHP Latch integration Alessandro Fanio March 7th

The world of Machine Learning is the object of a lot of talk lately. This webinar will analyze the use case of “Detecting anomalies in web traffic” with Isolation Forest algorithms. We’ll offer a practical vision by breaking down the details of how to use the Pandas datascience libraries and Scikit-Learn Machine Learning libraries, and resources like transformers and pipelines, that are so useful for transferring web traffic characteristics for analysis by the algorithms.

Find out more about this subject:
http://data-speaks.luca-d3.com/2017/06/luca-talk-redes-mas-seguras-machine.html