How to Achieve Optimal Performance: Code Optimisation in the AI ecosystem
Categories
Insights, Optimisation Lab

Boosting performance is a priority in the AI space. Businesses will not hesitate to make large investments to achieve even a marginal improvement (e.g. increased accuracy, speed) in AI systems. A range of factors impact the performance of AI; high-quality data, infrastructure, code, and the right talent are all crucial elements of a thriving AI […]

How Can Data Scientists Write Production-quality Machine Learning Code?
Categories
Insights, Optimisation Lab

[vc_row][vc_column][vc_column_text]Data science is a field that encapsulates a range of skills. However, in the data scientist’s toolbox, coding might become an underrated tool. In order to derive optimal results, a data scientist may choose to focus on a mathematical or conceptual component of their data science task. This strategy might reap greater benefits for tasks […]

How Can Complex Models Run Fast? Trade-off between model complexity and running speed
Categories
Insights, Optimisation Lab

There are several concerns when selecting machine learning models for a specific task. The model performance is of course a prime concern. Besides, the model complexity and speed are vital in scenarios requiring a fast deployment or quick response from models. In this article, we discuss the reasons behind fast and complex models, and how […]

What Is Imbalanced Data and How to Handle It?
Categories
Insights, Optimisation Lab

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 snippets Imbalanced data in practice […]

Four Methods to Statistically Measure Your Data Correlation
Categories
Insights, Optimisation Lab

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 […]

Data Quality in Machine Learning: How to Evaluate and Improve?
Categories
Insights, Optimisation Lab

Introduction 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 training process and result […]