If you’re a retailer looking for innovative approaches to engage customers, sometimes the answers are more available than you realize and found in evaluating company data. Data analysis provides insights to help you increase consumer engagement with the right products, services or messaging at the right time, through potentially multiple devices. However, evaluating large sets […]
Personalization Through Machine Learning Read More »
One of the most critical challenges with the data of the retailer is to determine the substitutable product pairs, usually online. While we apply machine learning approaches, it should involve assortment optimization engines to generate outcomes. The shopping experience is definitely ruling the brick and mortar stores, however, the rise of online shopping has revolutionized
When Substitution Models Go Wrong Read More »
Machine learning pipelines are used to optimize and automate the end-to-end workflow of a machine learning model. Core elements of the machine learning process can be refined or automated once mapped within a machine learning pipeline. As more and more organizations leverage the power of machine learning, models are developed and deployed within increasingly diverse
What is a Machine Learning Pipeline? A Step By Step Guide Read More »
Machine learning is increasingly becoming an integral part of the modern digital landscape, with models being deployed in more industries and organizations than ever before. An exponential increase in the amount of data being collected by organizations has increased the complexity of processing this data. But the potential value an organization can extract from ever-more
MLOps: What is it and Why it Matters Read More »
The implementation and growth of open source software (OSS) across business functions and geographies has had many positive impacts making it sometimes worth the hidden risks, in particular to help businesses to quickly develop new processes faster. OSS is generally free, making it popular for teams wanting quick results without budget sign-off or the fear
Open Source Machine Learning : Managing the Hidden Risks Read More »
Reinforcement learning is a method of training machine learning models through trial and error and feedback. The model will be given a goal and list of known actions. The model’s input is the measurement of its environment and current state, and output is the model’s action to move between states. Positive or negative reward signals are released
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Machine learning algorithms learn to make predictions or decisions by learning, from historical data, a model of the underlying process connecting inputs (a.k.a. features) and outputs (a.k.a. labels). If this process underlying the data remains unchanged throughout a model’s lifetime then its performance is likely to remain stable over time. However, if the process changes
Whether being used to clean data, surface trends and insights, or make forecasts, machine learning is increasingly becoming an important tool for data analytics. Organisations are processing more data than ever, so naturally want to harness this data to make decisions. Data analytics is the process of gaining insight and actions from data. As organisations gain
Machine Learning in Analytics Read More »
As machine learning gains traction across industries, businesses are finding new and novel uses for the technology. However, as soon as your organization moves beyond a handful of models, management and observability of this growing system can become a significant challenge. This is where the machine learning maturity model plays a part. Without proper monitoring,
Understanding the Machine Learning Maturity Model Read More »
Building walls to tear them down Traditional FSI organizations have silos due to regulatory, legal and operating pressures. Business units and functions try to unify across customer journey transformations to stop the short-term fix of stitching processes and data flows together to bridge customer touch points, often unsustainable, carrying higher cost implications further down the
Breaking Down Machine Learning Silos to Maximize Value Read More »
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