What is Machine Learning?
Machine learning (ML) is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without human intervention.
The process involves using statistical based algorithms built into computer programs to find patterns, and derive meaning from large amounts of data. The goal is for the program to make a decision in the future based on the patterns/meaning learnt from the observations of data. Improved decisions are made as new observations of data are made available to the program to learn.
Machine learning is often shrouded in mystery. Most organisations are excited about its potential, but require help to understand and integrate it into their existing business processes in order to reap benefits from the technology.
Machine learning is a relatively new field, where methodologies and processes lack standardization and consistency. As a consequence, from ideation to productization, the machine learning process is lengthy with no guarantee of results.
Complex and experimental - Organisations become discouraged when they are unable to demonstrate results, benefits and return on investment (ROI) related to machine learning initiatives.
AugustAi is an industry-proven automated machine learning platform in the structured data space that solves these challenges.
It uses simplicity, standardisation, speed and scale in the cloud to build predictive models, whilst maintaining precision and visibility over machine learning business decisions, benefits and ROI.
All you need is data, and AugustAi will handle the rest. AugustAi is able to very quickly integrate with your technology ecosystem, digest large amounts of data and produce a machine learning model in the matter of minutes.
For example, AugustAi has the ability to process up to ~8 million rows, and ~1,000 columns of customer data, to produce highly accurate ML models and insights for 2-3 use cases, in the matter of 2-3 hours.
The platform combines Agile methodologies with MLOps in the cloud to simplify, and streamline the machine learning ideation to productization process, at speed and at scale.
What We Do Differently
Most machine learning systems are on equal footing, and automated machine learning platforms offer up similar functionality. Automation is nothing without Control. Control is nothing without Visibility.
AugustAi orchestrates Control and Visibility with Automation and Model Explainability.
Control - Allows Data Scientist to control, configure, version and run every step of the ML process
Visibility - Metrics, statistics, analytics and insights from every ML step. Model explainability feature eliminates the “black box” nature of machine learning
Automation - Data scientists have the capability to run the ML process automatically, or Control every step. Artifacts generated on a preceding ML step is fed into the ML next step
Market leaders have recognised that:
Machine learning and AI have demonstrated benefits and value in an organisation
Standardization & automation of ML drive speed, scale and efficiencies
Teams become productive in their day jobs
Giving them the capacity to innovate
Allowing for breakthroughs and discoveries
Which improves and matures Machine Learning in an organisation
And increases return of investment
Potential Use Cases
Customer acquisition; Product graduation / cross-sell; Customer churn; Customer Segmentation; Customer issue management; Customer sentiment; Market / location optimisation; Sales forecasting; Margin optimisation; Shelf display optimisation; Product loyalty and uptake.
Risk: Fraud management; Risk mitigation.
Operations: Manufacturing optimisation / demand management / predictive maintenance; Procurement optimisation; Inventory management; Driver fatigue & accident prevention; Optimise production logistics; Debt collection optimisation.
People: Employee churn; OH&S.
Marketing: Customer loyalty; Customer ROI; Sentiment; Effectiveness of marketing campaign.
Water management; End consumer waste minimisation; Energy use optimisation; Ethical sustainability rating.