anomaly detection
background

Using common statistical methods to model what is normal is a fairly straightforward task for systems with simple data patterns, but building more complex systems can present a considerable challenge.

business challenges

The task was to find unusual, rarely occurring events or data for which little is known in advance. Anomalies are defined not by their own characteristics but in contrast to what is normal and they spoiled the regular processing cycle.



value delivered

We've been able to build a highly accurate detector of anomalies. It helped to: (a) speed up a regular processing algorithms, (b) find algorithm defects, (c) increase system stability, and (d) create a customized processing routine which takes care of anomalies.



approach

We've provided an effective way of to measure similarity between samples using generative models for likelihood estimation.


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our expertise in

AI technologies

data mining

PCA
K-means
Decision trees
Linear models
PageRank

digital signal processing

Digital filters
DTW

machine learning

Deep learning
Probabilistic graphical models
CART
ensembles
unsupervised sound segmentation
recurrent models
bayesian approach
probabilistic programming
hmm

image processing and
computer vision

alexnet
vgg
vae

natural language
processing

PCA
TF-IDF
LDA
SVM
Naive bayes
word2vec
attention models

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about us

Hi, we are Sciforce - a company where the integration of various branches of science builds up a powerful force to create robust software solutions. Working at the intersection of Computer Science with other technical, natural and humanitarian sciences let us go beyond traditional IT services and become both technical and scientific forces to our customers.