This is part of Machine Learning-Driven Anomaly Detection
What you will learn
Since the data is autoregressive, these algorithms use recent past data to predict anomaly.
Will be discussing
- Forecast based anomaly detection
- Decomposition based anomaly detection
- Dissimilarity based anomaly detection
- Markov chain based anomaly detection
- Ngram frequency based anomaly detection
- Segment based anomaly detection
This is a FREE class!
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
COO, CIO, DevOps, Software Engineers
- 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
- Class Notes here
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.