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Transform Global Speech Into Local Language with TalkLocal
Imagine being able to understand every word spoken in your native tongue at a conference or meeting that is being held in a language that is unfamiliar to you. A system of such nature can instantly transcribe spoken utterances into text using sophisticated automatic speech recognition(ASR)... Read more
Low Code Time Series Analysis
Time Series Forecasting is a unique field in Machine Learning. When working with time series in fact there is an inherent time dependency between the different points in the series and therefore the different observations are highly dependent on each other. If you are interested in... Read more
Upholding Data Quality in Machine Learning Systems
In the dazzling world of machine learning (ML), it’s quite effortless to get engrossed in the thrill of devising sophisticated algorithms, captivating visualizations, and impressive predictive models. Yet, much like the durability of a building depends not just on its visible structure but also its hidden... Read more
Feature Store Architecture and How to Build One
As machine learning becomes increasingly integral to business operations, the role of ML Platform Teams is gaining prominence. These teams are tasked with developing or selecting the essential tools that enable machine learning to move beyond experimentation into real-world applications. One such indispensable tool is a... Read more
Organizational Processes for Machine Learning Risk Management
In our ongoing series on Machine Learning Risk Management, we’ve embarked on a journey to unravel the critical elements that ensure the trustworthiness of Machine Learning (ML) systems. In our first installment, we delved into “Cultural Competencies for Machine Learning Risk Management,” exploring the human dimensions... Read more
Evaluating Clustering in Machine Learning
Clustering has always been one of those topics that garnered my attention. Especially when I was first getting into the whole sphere of machine learning, unsupervised clustering always carried an allure with it for me. To put it simply, clustering is rather like the unsung knight... Read more
Data Engineering vs Machine Learning Pipelines
Data engineering and machine learning pipelines are both very different but oddly can feel very similar. Many ML engineers I have talked to in the past rely on tools like Airflow to deploy their batch models. So I wanted to discuss the difference between data engineering... Read more
How to Practice Data-Centric AI and Have AI Improve its Own Dataset
Editor’s note: Jonas Mueller is a speaker for ODSC West this October 30th to November 2nd. Be sure to check out his talk, “How to Practice Data-Centric AI and Have AI Improve its Own Dataset,” there! Machine learning models are only as good as the data... Read more
How Machine Learning Can Be Used to Cut Energy Bills
Utility companies are turning to machine learning to lower customers’ energy bills — and their own. They can offer better prices for consumers when overhead and operational costs are lower, creating a win-win situation for everyone involved. Here’s how machine learning and AI are making power... Read more
Machine Learning Engineering in the Real World
The majority of us who work in machine learning, analytics, and related disciplines do so for organizations with a variety of different structures and motives. These could be for for-profit corporations, not-for-profits, charities, or public sector organizations like the Government or Universities. In pretty much all... Read more