How to Achieve Optimal Performance: Code Optimisation in the AI ecosystem

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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?

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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

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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 […]

Fast Hyperparameter Tuning to Improve Model Performance

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Image by Daniel J. TOTH Hyperparameter tuning plays an important role in the process of training an optimal machine learning model. During the training process, the performance of the target model is evaluated by monitoring metrics such as the values of the loss function or the accuracy score on the test/validation set, on which basis […]

What Is Imbalanced Data and How to Handle It?

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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

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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 […]

Feature Generation: what it is and how to do it?

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In our everyday life we are faced with decisions. One of the reasons why we struggle to take a decision is because, most of the time, it involves more than one objective. For instance, when buying a car, it isn’t just about buying the best car; but about buying a car that you can afford, […]

Data Quality in Machine Learning: How to Evaluate and Improve?

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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 […]