ODSC - Open Data Science

DECEMBER 13, 2023

The AI used by the DeepMind team was trained on data from the Materials Project. That’s an international research group founded at the Lawrence Berkeley National Laboratory in 2011. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

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Pickl AI

JULY 12, 2023

Data Science Movies has been sprawling in the sector since years now, and people have started to understand its significance today. Numerous movies have been produced and made that enables you to understand the ways in which Artificial Intelligence, Machine Learning, Data and Information have played crucial roles.

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ODSC - Open Data Science

FEBRUARY 20, 2023

As newer fields emerge within data science and the research is still hard to grasp, sometimes it’s best to talk to the experts and pioneers of the field. He gave the Inaugural IMS Grace Wahba Lecture in 2022, the IMS Neyman Lecture in 2011, and an IMS Medallion Lecture in 2004. Recently, we spoke with Michael I.

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DataRobot

FEBRUARY 10, 2021

Even if all the code runs and the model seems to be spitting out reasonable answers, it’s possible for a model to encode fundamental data science mistakes that invalidate its results. As a data scientist, one of my passions is to reproduce research papers as a learning exercise. See the source for this graphic.).

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Towards AI

NOVEMBER 8, 2024

Edited Photo by Taylor Vick on Unsplash In ML engineering, data quality isn’t just critical — it’s foundational. Since 2011, Peter Norvig’s words underscore the power of a data-centric approach in machine learning. This member-only story is on us. Upgrade to access all of Medium.

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NYU Center for Data Science

SEPTEMBER 11, 2024

I’m excited to be part of CDS because it provides a unique environment where cutting-edge data science methods can be developed and applied to push the boundaries of science,” said Ho. “I I look forward to collaborating with fellow researchers and students to explore new frontiers in foundation models for science.”

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AWS Machine Learning Blog

MAY 10, 2023

Project Jupyter is a multi-stakeholder, open-source project that builds applications, open standards, and tools for data science, machine learning (ML), and computational science. Given the importance of Jupyter to data scientists and ML developers, AWS is an active sponsor and contributor to Project Jupyter.

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Data Science Blog

JUNE 27, 2023

In the realm of Big Data, there are two prominent architectural concepts that perplex companies embarking on the construction or restructuring of their Big Data platform: Lambda architecture or Kappa architecture. Its focus on unique, ongoing events allows for effective and responsive data processing.

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ODSC - Open Data Science

MAY 2, 2023

There are plenty of data science or data analytics degrees available for those looking for a traditional education approach to learning a new skill. This year we’re welcoming some great data analytics degrees education partners to ODSC East.

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ODSC - Open Data Science

JUNE 6, 2023

Since 2011, a man by the name of Gert-Jan Oskam had been paralyzed from the hips down after a motorcycle accident. You can also get data science training on-demand wherever you are with our Ai+ Training platform. Due to the accident, his spine had become injured and communication between it and his brain had been broken.

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IBM Data Science in Practice

JULY 5, 2023

Nucleic Acids Research, 40(D1):D1100–D1107, 09 2011. Sci Data 10, 67 (2023). Otter-Knowledge was originally published in IBM Data Science in Practice on Medium, where people are continuing the conversation by highlighting and responding to this story. Overington. ISSN 0305–1048. doi: 10.1093/nar/gkr777. Huang, K. &

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Universe of Data Science

FEBRUARY 26, 2022

Thirdly, we use Grubbs test to test whether outliers are present in data. Chi-squared, Dixon and Grubbs tests are available in outliers R package (Komsta, 2011). How to Test for Identifying Outliers in R Using RStudio Subscribe to YouTube Channel Don’t forget to check: How to Clean Data in R References Komsta, L. Millard, S.P.

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Alation

FEBRUARY 20, 2020

Analyst Michelle Goetz, a well known advisor to enterprise architects, chief data officers, and business analysts, has been tracking this market for some time. She’s seen the evolution of the self-service analytics market from decision systems to business intelligence to data visualization to data science and automated intelligence.

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Precisely

FEBRUARY 9, 2023

Science and technology have evolved rapidly since then, providing far more granular data, reflecting what is happening at a much more localized level. Today, data science enables you to understand the real-world impact of weather events as they happen.

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Precisely

FEBRUARY 9, 2023

Science and technology have evolved rapidly since then, providing far more granular data, reflecting what is happening at a much more localized level. Today, data science enables you to understand the real-world impact of weather events as they happen.

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Hacker News

MARCH 18, 2025

Then in 2022 a nice book on the Game of Life came out (by Nathaniel Johnston and Dave Greene, the latter of whom had actually been at our Summer School back in 2011 ). But the project of studying the metaengineering of the Game of Life stayed on my to do list (and a couple of students at our Wolfram Summer School worked on it).

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AWS Machine Learning Blog

APRIL 19, 2023

The resulting training dataset from the processing job can be saved directly as a CSV for model training, or it can be bulk ingested into an offline feature group that can be used for other models and by other data science teams to address a wide variety of other use cases.

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AWS Machine Learning Blog

MAY 2, 2023

There are a few limitations of using off-the-shelf pre-trained LLMs: They’re usually trained offline, making the model agnostic to the latest information (for example, a chatbot trained from 2011–2018 has no information about COVID-19). They’re mostly trained on general domain corpora, making them less effective on domain-specific tasks.

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Mlearning.ai

AUGUST 6, 2023

As described in the previous article , we want to forecast the energy consumption from August of 2013 to March of 2014 by training on data from November of 2011 to July of 2013. Experiments Before moving on to the experiments, let’s quickly remember what’s our task.

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Mlearning.ai

FEBRUARY 27, 2023

For the purposes of this tutorial, I’ve chosen the London Energy Dataset which contains the energy consumption of 5,567 randomly selected households in the city of London, UK for the time period of November 2011 to February 2014.

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Heartbeat

OCTOBER 9, 2023

Editor's Note: Heartbeat is a contributor-driven online publication and community dedicated to providing premier educational resources for data science, machine learning, and deep learning practitioners. Here are some resources for more information: Hasibuan, Z. Ahmad, M., & Selviandro, N. Ekanayake, B.,

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DagsHub

JULY 25, 2024

In 2011, H2O.ai Companies like PayPal , Wells Fargo , and MarketAxess leverage H2O.ai's machine learning capabilities to drive data science initiatives. is suitable for enterprises and data scientists looking to accelerate their machine-learning workflows with automated tools and scalable solutions.

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Heartbeat

JULY 27, 2023

jpg': {'class': 111, 'label': 'Ford Ranger SuperCab 2011'}, '00236.jpg': jpg': {'class': 102, 'label': 'Ferrari California Convertible 2012'}, Since this isn’t an article on data cleaning/preparation, for this initial step, I’m just going to show my code with comments.

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