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Ntropy blog

4.28.22

Ntropy Custom Models

Same Powerful Transaction API; New Custom Categorization

4.27.22

Using Elyra to create Machine Learning pipelines on Kubeflow

A framework that makes it easy to create pipelines and run them on existing pipeline platforms.

4.19.22

Customized Transaction Classification

Successes, benchmarking, and how to maximize your performance. Bringing meta-learning to production.

4.3.22

Speeding up Cross-encoders for both Training and Inference

We present how we use cross-encoder transformers and attention masking for superior performance

3.19.22

Multilingual Named Entity Recognition for Financial Transactions

How we were able to achieve the best accuracy for multilingual named entity recognition.

3.17.22

Hard Problem, Simple Solution: Categorizing Data from Financial Transactions

Categorizing Data from Financial Transactions matters. Here’s how you do it and why it’s important.

3.3.22

War in Ukraine

We could not stay silent about what is going on in Ukraine. Here is what we are doing to support

2.25.22

Evolving an API while keeping backwards compatibility

Maintaining backwards compatibility is one side of the coin. The other issue is to make sure the new

2.20.22

Quickly finding recurring events in massive sequences

A scalable O(N*K) solution for sequences of size N and max intervals of size K.

2.4.22

Clustering millions of sentences to optimize the ML-workflow

Practical use cases of sentence clustering.

1.23.22

How we reduced our infrastructure costs by 8x without sacrificing performance

How we leveraged open-source and cloud providers to lower training costs and decrease training time.

12.28.21

Deep ML cannot be built in-house

We have heard multiple arguments that ML should be built in-house.

12.21.21

Transaction data is an uncut gem

Our favorite use cases for a transaction categorization API

12.12.21

Understanding financial transactions

What is transaction categorisation and why is it important?

12.12.21

A castle getaway: the Ntropian offsite

Our first meeting IRL

6.1.21

The Ntropy API

The Ntropy API enables companies to understand financial transactions with super-human accuracy.

5.20.21

No-data ML

Can machine-learning models be deployed to production from day one, with nearly no internal data?

4.24.20

Dissolving data silos

The benefits of bridging data silos.

4.24.20

The unreasonable effectiveness of combining datasets

A machine learning model generally gets more and more accurate with more data.

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