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IBM and Microsoft partnership accelerates sustainable cloud modernization

IBM Journey to AI blog

According to the IT Sustainability Beyond the Data Center report from the IBM Institute for Business Value, some estimates suggest that there has been a 43% absolute increase in the power capacity demand by data center operators between 2018 and 2021, and that the global data center market will grow by more than 30% between 2021 and 2027.

Azure 98
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How to optimize your LinkedIn as a Data Scientist?

Pickl AI

Data Scientist LinkedIn Profile Example Marla Smith, Senior Data Scientist at ABC Company Summary: Experienced data scientist with a strong background in statistical analysis, machine learning, and data visualization. Passionate about leveraging data to drive business decisions and improve customer experience.

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Visualizing the Tour de France in the year I tackle the route

Cambridge Intelligence

In the lead up to this, my day job as a software developer gave me a break from hard training rides, but my love of cycling sparked a mini side project: building web apps with the data visualization tools I help to develop, and using them to analyze and visualize Tour de France data.

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5000x Generative AI: Intro, Overview, Models, Prompts, Technology, Tools, Comparisons & the Best…

Mlearning.ai

Traditional AI can recognize, classify, and cluster, but not generate the data it is trained on. Their generative sisters, on the other hand, are pre-trained on giant amounts of data from human domains. Let’s play the comparison game. Classic AI models are usually focused on a single task. Image credit: Yang, Jingfeng et.

AI 98
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Linear Regression for tech start-up company Cars4U in Python

Mlearning.ai

In 2018–2019, while new car sales were recorded at 3.6 These are common Python libraries used for data analysis and visualization. The next step post that would be to cluster different sets of data and see if multiple models should be created for different locations and car types. I hope you enjoyed this post.

Python 52
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Analyzing the history of Tableau innovation

Tableau

VizQL’s powerful combination of query and visual encoding led me to the following six innovation vectors in my analysis of Tableau’s history: Falling under the category of query , we’ll discuss connectivity , multiple tables , and performance. April 2018), which focused on users who do understand joins and curating federated data sources.

Tableau 145
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Analyzing the history of Tableau innovation

Tableau

VizQL’s powerful combination of query and visual encoding led me to the following six innovation vectors in my analysis of Tableau’s history: Falling under the category of query , we’ll discuss connectivity , multiple tables , and performance. April 2018), which focused on users who do understand joins and curating federated data sources.

Tableau 98