Anomaly Detection Session 1: Exploratory data analysis using python to discover the category of data
Overview
This is part of Machine Learning-Driven Anomaly Detection
In this session, you will learn what exactly is anomalous data? Is it extreme values or rare values? We will run various data exploration techniques using various python libraries to determine what kind of data we have. Once that determination has been made we will be able to choose the right anomaly detection algorithm.
This is a FREE class!
On-Demand
Can’t make it to live session? No worries. Go ahead and register; we will send you the session recording .
See below for past session recordings & notes
What you will learn
- Why exploratory data analysis(EDA) is important for anomaly detection
- What kind of anomaly detection algorithms to use for anomaly detection based on EDA
Intended Audience
COO, CIO, DevOps, Software Engineers
Prerequisites
- Must have: Development experience
- Nice to have: Python knowledge
What to Bring
- Please bring a reasonably modern laptop (Corporate laptops with overly restrictive firewalls may not work well; Personal laptops are recommended)
- [nice to have] download our docker image elephantscale/es-training
Session Recording
Presenter
Pranab Ghosh
Pranab Ghosh is a Data Science Consultant, He owns several open-source Big Data and Data Science projects using Hadoop, Spark, Storm, Kafka, NoSQL databases, and the related ecosystem.
Linkedin: https://www.linkedin.com/in/pkghosh/