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Get insights & best practices into AI & machine learning to drive data transformation, upskill, and build data cultures. Discover how you can use ML in your work.
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Top articles you may have missed last month
This article covers major news and updates from the field of data science and machine learning that happened last month. Spanning different topics such as tutorials, research, new packages, use cases, and more.
Anuj Syal
April 29, 2022
10 Awesome Resources for Learning MLOps
MLOps combines tools, practices, techniques, & culture that ensure the reliable and scalable deployment of machine learning models. Start your learning journey with these awesome free resources.
Ani Madurkar
March 30, 2022
MLOps Best Practices and How to Apply Them
Learn the key best practices of a successful MLOps practice and how it ensures reliable and scalable deployment of machine learning systems
Adel Nehme
March 30, 2022
Getting Started with MLOps
Learn about the rise of MLOps and how to get started with a comprehensive set of resources
Hajar Khizou
March 30, 2022
Data Science in Marketing: Customer Churn Rate Prediction
Learn how to use Python machine learning models to predict customer churn rates, turning marketing data into meaningful insights.
Elena Kosourova
March 28, 2022
Data Science in Sales: Customer Sentiment Analysis
Learn how data science can be used to analyze customer emotions and deliver valuable insights for sales optimization.
Elena Kosourova
March 23, 2022
Data Science in Banking: Fraud Detection
Learn how data science is implemented in the banking sector by exploring one of the most common use cases: fraud detection.
Elena Kosourova
March 21, 2022
The Past, Present, and Future of MLOps
MLOps is not just for data experts but for everyone from data teams to SMEs and to IT. Here's the rundown on why MLOps is important, what problems it aims to solve, and how in this jargon-free blog post.
Kevin Babitz
July 30, 2021
GPT-3 and the Next Generation of AI-Powered Services
How GPT-3 expands the world of possibilities for language tasks—and why it will pave the way for designers to prototype more easily, streamline work for data analysts, enable more robust research, and automate content generation.
Adel Nehme
November 6, 2020
How to Ethically Use Machine Learning to Drive Decisions
Having good quality data requires strong data foundations, along with a commitment to monitoring models and removing bias.
Joyce Chiu
August 31, 2020
Measuring Bias in Machine Learning: The Statistical Bias Test
This tutorial will define statistical bias in a machine learning model and demonstrate how to perform the test on synthetic data.
DataRobot Inc
May 5, 2020
How to Make Time for Learning—Without Losing Productivity
Find out how to prioritize continuous learning to influence business outcomes and reach your own professional goals.
Joyce Chiu
May 4, 2020