Model Training

Train machine-learning models across large data sets, then inspect and fine-tune their performance for reliable results in production.

Ελληνική έκδοση

Models that learn from all your data

Training at big-data scale

Set algorithms that work across large sets of data to train your models, then inspect and fine-tune their performance.

Distributed training on the Hadoop ecosystem means your models learn from your complete history rather than a sample, and can be retrained on fresh data as your business changes.

Machine learning model training

What we deliver

From data preparation to a trained model you can deploy and trust.

Data Preparation

Select, clean and label training data, and engineer the features your model needs.

Supervised & Unsupervised Learning

Classification, regression, clustering and anomaly detection, matched to your problem.

Distributed Training

Train on full data sets with Apache Spark across a cluster instead of a single machine.

Model Tuning

Hyper-parameter tuning and feature selection to reach the best accuracy for your budget.

Evaluation & Inspection

Measure performance on held-out data and inspect results, so you know how the model behaves before go-live.

Trained Model & Retraining

Versioned, deployable models with scheduled retraining as new data arrives.

Machine learning in production since 2017

In 2017 a mobile operator asked us to screen the content of 120 million SMS a day, in real time, for fraud and phishing, in a language our team did not speak.

Machine learning made it possible, and we have been building ML and AI systems ever since. Today we bring the same experience to training models on our clients’ data at big-data scale.

M
SMS screened per day
2000
Machine learning in production since

Built on the Hadoop ecosystem

Training pipelines run on Apache Spark and YARN over HDFS and Delta Lake, with Apache Airflow scheduling every data-preparation, training and retraining run.

How we work

A repeatable training cycle that keeps your models accurate over time.

1. Prepare

Prepare your data and split it into training, validation and test sets.

2. Train & Tune

Train candidate models and fine-tune them against the metrics that matter to you.

3. Deploy & Retrain

Deliver the trained model into your application and keep it current with scheduled retraining.

Explore our Data & AI services

Each service stands on its own, and together they take you from raw data to AI in production.
Predictive analytics and machine learning on big data

Model Development

Predictive and machine-learning models for forecasting, scoring and anomaly detection, built on big data.

AI model training on GPUs

AI Model Training

Train and fine-tune deep-learning models and LLMs on our in-house GPUs, with data collected at scale.

Data cleansing

Data Cleansing

Eliminate errors and inconsistencies with automated cleansing pipelines that keep your data reliable.

Ready to put your data to work?

Tell us about your data and your goals, and our experts will propose the right approach.