Tech Corner

Responsible AI Series: Part 3

In this mini-series, we are investigating three different model-agnostic machine learning interpretability techniques offered by the MathWorks product suite. In this third piece we shall look at the use of Shapley values.

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Smart Mining & Manufacturing: Building your own Object Detection Model

In this post we will highlight the AI modeling stage where we create our object detection model using tools in MATLAB. We will first explain some concepts that deal with object detection then finally we will create, train, and test an object detection model that will be able to detect craters on the surface of the moon in real-time.

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Making sense of the Lockdown Climate Through Data Driven Insights

OVERVIEW The year 2020 was characterised by a lot of uncertainty which was largely brought about by the Coronavirus pandemic. [...]

Smart Mining & Manufacturing: Dealing with “Really Big” Images

Over the next few posts, we will be looking at using deep learning for object detection. In the object detection [...]

Enhancing Product Development in Telecommunication

Successfully overcoming obstacles in the process of developing a product while managing the product development workflow is an art. The [...]

Responsible AI Series: Part 2

In this mini-series, we are investigating three different model-agnostic machine learning interpretability techniques offered by the MathWorks product suite. These [...]

Responsible AI Series: Part 1

In this mini-series, we are investigating three different model-agnostic machine learning interpretability techniques offered by the MathWorks product suite. These [...]

Smart Mining & Manufacturing: Data Access and Pre-processing for Computer Vision Applications – Common Challenges

Recent developments in deep learning have significantly improved our ability to detect defects. In the Automated Vision-Based Inspection and Defect [...]

Smart Mining & Manufacturing: Anomaly Detection and localisation using Variational Autoencoder (VAE)

In the previous post we did a webinar on how you can perform Automated Vision-Based Inspection and Defect Detection using [...]

Smart Mining & Manufacturing –  Automated Vision-Based Inspection and Defect Detection for Industrial Applications

Vision-based detection and tracking algorithms have evolved significantly over the past ten years. Where features used to be engineered, they [...]

Fraud Detection in Online Banking Data

Digital banking fraud resulted in a total financial loss of R284.2m in 2019, an 8% increase from 2018 [1]. The [...]

Effective Data Management in Business

At Opti-Num we have seen the importance of effective data management within business. Data is at the corner stone of [...]

Cost Effective Customer Retention Strategies using Offer Tiers

Retaining customers is a difficult task no matter which industry of operation, especially in tough economic conditions when the market [...]

Parallel Paradise: How to Speed up your Code

Verushen Coopoo, Applications Engineer Opti-Num Solutions, 2020 In this article we demonstrate the benefit that parallel computing resources can offer [...]

Preparing Big Data for Analytics: Best Practice from Opti-Num Solutions

The technical team at Opti-Num Solutions have experience working with all types of data, using various techniques to deliver insight [...]

Part 7: Deploy and Integrate Your Predictive Maintenance Model into Your Organisation in Various Ways

Predictive Maintenance is important to many organisations in the mining and manufacturing industries because it results in tangible operations improvement. [...]

Implied volatility surface generation using autoencoders in MATLAB

An essential tool used in the pricing of options is the implied volatility (IV) surface. A problem faced when trying [...]

Part 6: Predictive Maintenance Using an Unlabelled Dataset

In the previous article we went through a supervised learning approach for Predictive Maintenance. However, with a conservative maintenance schedule [...]

Weathering the Storm: An Introduction to Climate Risk with MATLAB

Melting polar ice caps, a depleting ozone layer and rising oceanic temperatures aren’t the only things affected by climate change [...]

Forecasting and Prediction: An Advanced Business Analytics Case Study

Opti-Num Solutions Advanced Business Analytics Team was approached by a telecommunications company to recommend and implement pricing strategy changes on [...]

Text Analytics for data-driven decision making

Text Analytics is a technique used to understand consumer’s opinions regarding products and services. The way people discuss their experience on public platforms, such as social media and blogs, provides insights for businesses on how to adapt [...]

Modelling with Categorical Variables

Building predictive models or analysing data to glean insights from the data is relatively easy when working with numerical data. [...]

Part 5: Predictive Maintenance Using a Labelled Dataset

In this article we look at a practical example of Predictive Maintenance where we are given synthetic data from a [...]

Explainability for machine learning models in MATLAB

As artificial intelligence becomes more prevalent in financial industries, its use presents considerable opportunities but also challenges. AI models have [...]

Part 4: Four Common Obstacles of Predictive Maintenance

Predictive maintenance has a lot of benefits, from reducing unplanned downtime, lowering maintenance costs to extending equipment life. It is no wonder maintenance managers are looking to apply these technologies to their processes.  In this series, we started [...]

Premier League Prediction Using Deep Learning

The English Premier League is one of the world’s most hotly contested footballing competitions, in which 20 teams battle it [...]

Automation for Downloading, Processing and Extraction of CPI Data

Increased consumer expectations and aggressive competition for a finite customer pool are driving service fees down substantially. Executives are driving [...]

Part 3: How to Estimate Remaining Useful life with MATLAB

The purpose of Predictive Maintenance is to estimate the Remaining Useful Life (RUL) of your equipment. RUL is the length of time your equipment is likely to operate before it requires repair [...]

Machine Learning for Fundamental Analysis

In South Africa, the number of businesses listed on the JSE is few compared to some international stock exchanges, therefore [...]

Part 2: Using Condition Indicators for Predictive Maintenance

Knowing how to predict equipment failure, rather than just reacting to failure, can mean significant benefits for your business, from reduced downtimes to extended equipment life! When looking at [...]

An Approach to Advanced Business Analytics

At Opti-Num Solutions, we believe in walking the journey with our clients as we work together to bring vision to [...]

Feature Selection made easy with ‘screenpredictors’

Pre-processing of features or predictor variables for the development of machine learning models is usually a tedious process. The MathWorks [...]

Part 1: What is Predictive Maintenance?

Equipment used in the mining and manufacturing industries can fail without warning, which leads to unplanned downtime, higher maintenance costs [...]

Constucting the Optimal Portfolio with MATLAB and Smart Beta

Verushen Coopoo, Application Engineer Opti-Num Solutions (2019) In this script, we demonstrate the strength of MATLAB’s optimisation capabilities to construct [...]

SuperBru Predictions with AI

Congrats to the Boks! For the recent Rugby World Cup a few members of the Opti-Num team participated in a [...]

AI in Industry 4.0: I have all this sensor data… Now what?

Predictive maintenance uses data to monitor the condition of equipment. Using fourth industrial revolution techniques means reduced failures, less machine [...]

Drones: Reaching New Heights in Education

Are you looking to make your classes more relevant and engaging? Drones have increased functionality and have decreased in size, [...]