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30 Best Data Science Books to Read in 2023

Analytics Vidhya

Introduction Data science has taken over all economic sectors in recent times. To achieve maximum efficiency, every company strives to use various data at every stage of its operations.

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Unlocking the Power of AI with Implemented Machine Learning Ops Projects

Becoming Human

It covers everything from data preparation and model training to deployment, monitoring, and maintenance. The MLOps process can be broken down into four main stages: Data Preparation: This involves collecting and cleaning data to ensure it is ready for analysis.

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How OLAP and AI can enable better business

IBM Journey to AI blog

Security and compliance : Ensuring data security and compliance with regulatory requirements in the cloud environment can be complex. Skills and expertise : Transitioning to cloud-based OLAP may require specialized skills and expertise in cloud computing and OLAP technologies.

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TAI #109: Cost and Capability Leaders Switching Places With GPT-4o Mini and LLama 3.1?

Towards AI

Matt Holden noted on x/twitter that in the early days of cloud storage — in its first decade (2006–2016), Amazon S3 cost per GB of storage dropped 86% (or ~97%, including Glacier). The speed of AI cost reduction is dramatically faster, potentially enabling much more rapid adoption relative to cloud computing.

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Build an end-to-end MLOps pipeline using Amazon SageMaker Pipelines, GitHub, and GitHub Actions

AWS Machine Learning Blog

We create an automated model build pipeline that includes steps for data preparation, model training, model evaluation, and registration of the trained model in the SageMaker Model Registry. Pooya Vahidi is a Senior Solutions Architect at AWS, passionate about computer science, artificial intelligence, and cloud computing.

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The Top AI Slides from ODSC West 2024

ODSC - Open Data Science

Dimensional Data Modeling in the Modern Era by Dustin Dorsey Slides Dustin Dorsey’s AI slides explored the evolution of dimensional data modeling, a staple in data warehousing and business intelligence. Despite the rise of big data technologies and cloud computing, the principles of dimensional modeling remain relevant.

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Must-Have Skills for a Machine Learning Engineer

Pickl AI

Familiarity with cloud computing tools supports scalable model deployment. Data Transformation Transforming data prepares it for Machine Learning models. Encoding categorical variables converts non-numeric data into a usable format for ML models, often using techniques like one-hot encoding.