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Correlations is a measure of the association between variables. They measure to what extent one variable is affected by a change in another variable. In this article, we will explain the importance of data correlation in machine learning, and introduce four common methods to calculate your data correlation.

Why Data Correlation is Important?

Understanding which…

Imbalanced data is a common problem in machine learning, which brings challenges to feature correlation, class separation and evaluation, and results in poor model performance. In this article, we will introduce:

  • Imbalanced data in practice
  • Three challenges with imbalanced data
  • Top 6 data sampling techniques
  • Sampling techniques comparison
  • Python code…

With data being at the heart of machine learning, it is inevitable that the performance of all machine learning algorithms is directly affected by the quality of the input data. The saying Garbage in-Garbage out holds in the machine learning case as well: using bad quality data can mislead the…

Scaling AI means 4S: Scale, Speed, Scope and Sustainability.

This Earth Day, we spotlight on Green AI.

Scaling AI requires energy-efficient models to minimise ⚡️computing cost and 🌳environmental cost. EvoML automatically optimises AI models at code level to achieve optimal Energy Efficiency, without compromising accuracy or other business metrics.


Scaling AI means 4S: Scale, Speed, Scope and Sustainability.

This week, we spotlight on “SCOPE”.

Scaling AI means the pervasive use of AI by different teams, departments and for different use cases.

EvoML enables both tech and business users to generate accurate & efficient AI models instantly. With a high…

Scaling AI means 4S: Scale, Speed, Scope and Sustainability.

This week, we spotlight on Vol.2 SPEED.

Scaling AI requires organisations to build, run and adapt AI at speed.

With EvoML, businesses can:

  1. Automatically build hundreds of models in parallel, in hours or days
  2. Optimise models to run faster with our…

Scaling AI means 4S: Scale, Speed, Scope and Sustainability.

This week, we spotlight on Vol.1 SCALE.

There are difficult trade-offs between AI accuracy and efficiency. Only AI that runs fast and efficiently uses hardware can truly scale in the real world.

TurinTech’s Multi-objective Optimisation feature enables businesses to tackle difficult…

EvoML: Scalable End-to-end Data Science Lifecycle

1. Introduction:

The practice of building AI is rapidly becoming automated. Automated Machine Learning (AutoML) is the process of automating the time consuming, iterative tasks of machine learning model development. However, AutoML on its own cannot bring AI to life in the real business world. …

-Why AI Efficiency is Critical for Scaling AI


Artificial Intelligence (AI) is an iterative optimisation process to achieve multiple objectives.

In a real business world with resources constraints, there are many trade-offs to tackle before deploying AI in business processes. These include accuracy, model complexity, explainability, running speed, cost, etc.

Let’s simplify Optimal AI as the formula below…

Challenges to become a first-class AI organisation


AI is a game changer, but it will take time, scale and expertise to unlock its full potential and ROI.

Companies strategically scaling AI generate 5X ROI VS Companies unable to scale. 86% of executives believe they won’t achieve their growth objectives unless they can scale their AI. -Accenture



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