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A Comprehensive Guide on Hyperparameter Tuning and its Techniques

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Image designed by the author – Shanthababu Introduction Every ML Engineer and Data Scientist must understand the significance of “Hyperparameter Tuning (HPs-T)” while selecting your right machine/deep learning model and improving the performance of the model(s).

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10 Best AI Tools for Small Manufacturers (February 2025)

Unite.AI

This kind of functionality is especially useful for small manufacturers who often lack dedicated staff for data analysis the AI helps automate routine tasks and surfaces insights (like best-selling products or low stock alerts).

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From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams

Towards AI

From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams Photo by Parabol | The Agile Meeting Toolbox on Unsplash In this article, we will explore the essential VS Code extensions that enhance productivity and collaboration for data scientists and machine learning (ML) engineers.

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How Businesses Can Leverage Google’s AI Tech

Unite.AI

The Vertex AI platform has gained growing popularity among clients as it accelerates ML development, slashing production time by up to 80% compared to alternative methods. It offers an extensive suite of ML Ops capabilities, enabling ML engineers, data scientists, and developers to contribute efficiently.

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Data Science vs. Machine Learning: What’s the Difference?

Marktechpost

Key Components of Data Science Data Collection : Gathering raw data from various sources. Data Cleaning : Ensuring the data is usable and accurate. Data Analysis : Applying statistical methods to discover trends. Data Visualization : Presenting findings via charts and graphs.

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MLOps and the evolution of data science

IBM Journey to AI blog

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning.

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Map Earth’s vegetation in under 20 minutes with Amazon SageMaker

AWS Machine Learning Blog

Methods such as field surveys and manual satellite data analysis are not only time-consuming, but also require significant resources and domain expertise. This often leads to delays in data collection and analysis, making it difficult to track and respond swiftly to environmental changes.