Towards AI

AUGUST 16, 2023

Michael Dziedzic on Unsplash I am often asked by prospective clients to explain the artificial intelligence (AI) software process, and I have recently been asked by managers with extensive software development and data science experience who wanted to implement MLOps. MIT Press, ISBN: 978–0262028189, 2014. [2] Russell and P.

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IBM Journey to AI blog

NOVEMBER 13, 2023

Developed internally at Google and released to the public in 2014, Kubernetes has enabled organizations to move away from traditional IT infrastructure and toward the automation of operational tasks tied to the deployment, scaling and managing of containerized applications (or microservices ).

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Dataconomy

SEPTEMBER 27, 2023

Data science and analytics MCSA and MCSE certifications can also lead to roles in data science and analytics, such as data analyst, data scientist, or business intelligence developer. Data analysts collect, clean, and analyze data to extract insights that can help businesses make better decisions.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

We are actively working on extending our methods to additional domains, such as computer vision, but be aware that our efficiency improvements do not translate to all ML domains at this time. Graviton Technical Guide is a good resource to consider while evaluating your ML workloads to run on Graviton.

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DagsHub

APRIL 7, 2024

Image generated with Midjourney In today’s fast-paced world of data science, building impactful machine learning models relies on much more than selecting the best algorithm for the job. Data scientists and machine learning engineers need to collaborate to make sure that together with the model, they develop robust data pipelines.

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AWS Machine Learning Blog

JANUARY 13, 2023

To mitigate these challenges, we propose a federated learning (FL) framework, based on open-source FedML on AWS, which enables analyzing sensitive HCLS data. It involves training a global machine learning (ML) model from distributed health data held locally at different sites. Import the data loader into the training script.

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Ocean Protocol

FEBRUARY 1, 2024

We will only use 1 airport for this data challenge, though METAR is a standard score updated at each airport. The data we use for this challenge is Miami's historical METAR logs from 2014–2023. These AI/ML models become invaluable tools for aviation operations and safety by harnessing the extensive historical METAR data.

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Snorkel AI

MAY 24, 2023

The Future of Data-centric AI virtual conference will bring together a star-studded lineup of expert speakers from across the machine learning, artificial intelligence, and data science field. chief data scientist, a role he held under President Barack Obama from 2015 to 2017. Patil served as the first U.S.

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Snorkel AI

MAY 24, 2023

The Future of Data-centric AI virtual conference will bring together a star-studded lineup of expert speakers from across the machine learning, artificial intelligence, and data science field. chief data scientist, a role he held under President Barack Obama from 2015 to 2017. Patil served as the first U.S.

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Pickl AI

MAY 16, 2023

If you are a Data Scientist, then your LinkedIn profile should be flooded with information on Data Science’s latest development in this domain, such that it instantly garners the attention of recruiters as well as your contemporaries. In fact, these industries majorly employ Data Scientists.

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Chatbots Life

MAY 16, 2023

10Clouds is a software consultancy, development, ML, and design house based in Warsaw, Poland. Deeper Insights Year Founded : 2014 HQ : London, UK Team Size : 11–50 employees Clients : Smith and Nephew, Deloitte, Breast Cancer Now, IAC, Jones Lang-Lasalle, Revival Health.

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Heartbeat

APRIL 18, 2023

It was introduced in 2014 by a group of researchers (A. 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. Zisserman and K. Simonyan) from the University of Oxford.

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ODSC - Open Data Science

JANUARY 29, 2024

They design intricate sequences of prompts, leveraging their knowledge of AI, machine learning, and data science to guide powerful LLMs (Large Language Models) towards complex tasks. Data science methodologies and skills can be leveraged to design these experiments, analyze results, and iteratively improve prompt strategies.

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How to Learn Machine Learning

JULY 20, 2024

However, significant strides were made in 2014 when Lan Goodfellow and his team introduced Generative adversarial networks (GANs). Supported by Natural Language Processing (NLP), Large language modules (LLMs), and Machine Learning (ML), Generative AI can evaluate and create extensive images and texts to assist users.

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The MLOps Blog

OCTOBER 20, 2023

Jupyter notebooks have been one of the most controversial tools in the data science community. Nevertheless, many data scientists will agree that they can be really valuable – if used well. I’ll show you best practices for using Jupyter Notebooks for exploratory data analysis. Aside neptune.ai

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Explosion

MAY 17, 2023

In 2014 I started working on spaCy , and here’s an excerpt of how I explained the motivation for the library: Computers don’t understand text. This generative output could be a complete game-changer, finally delivering the “insights” that data science projects have generally over-promised and under-delivered.

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Heartbeat

AUGUST 21, 2023

GoogLeNet: is a highly optimized CNN architecture developed by researchers at Google in 2014. 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.

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Heartbeat

FEBRUARY 27, 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. We’re committed to supporting and inspiring developers and engineers from all walks of life.

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Heartbeat

OCTOBER 13, 2023

Time series Analysis showing Tuberculosis morbidity from a timespan of January 2004 to June 2014 in Xinjiang. The Data was obtained from the website of the Bureau of Health, Xinjiang Uyghur Autonomous Region, China. The tuberculosis morbidity has roughly seasonal fluctuations and a slightly rising trend.

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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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Heartbeat

OCTOBER 9, 2023

References: Francesco Nex and Fabio Remondino's "Photogrammetry and Remote Sensing with Unmanned Aerial Vehicles" (2014). 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.

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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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Mlearning.ai

FEBRUARY 11, 2023

2014) Flask Web Development. References: Dwyer, G., Aggarwal, S. and Stouffer, J. 2017) Flask: Building Python Web Services. Packt Publishing. Available at: [link] (Accessed: 30 August 2022). Grinberg, M. Developing Web Applications with Python. O’Reilly Media. Available at: [link] (Accessed: 25 September 2022). BECOME a WRITER at MLearning.ai

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Mlearning.ai

FEBRUARY 28, 2023

Year: More than half the cars in the data were manufactured in or after 2014. Brand: Most of the cars in the data belong to Maruti or Hyundai. The log transformation was applied on this column to reduce skewness. Seats: 84% of the cars in the dataset are 5-seater cars. The price of used cars has increased over the years.

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Data Science Blog

MARCH 19, 2024

Mit dem integrierten autoML-Tool von TurinTech können Anwender zudem durch den Einsatz von ML-Modellen die Performance ihrer Abfragen direkt in ihrer Datenbank maximieren. So gelingt BI-Teams echte Datendemokratisierung und sie können mit ML-Modellen experimentieren, ohne dabei auf Support von ihren Data-Science-Teams angewiesen zu sei.

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Data Science Blog

JULY 9, 2024

Doch veraltete Legacy-Systeme verlängern Abfragezeiten und erschweren Echtzeitanalysen großer und komplexer Datenmengen, wie sie etwa für Machine Learning (ML) erforderlich sind. Die Kombination von KI, Data Analytics und Business Intelligence (BI) ermöglicht es Unternehmen, das volle Potenzial ihrer Daten auszuschöpfen.

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DrivenData Labs

SEPTEMBER 10, 2024

Winning teams included individuals with expertise in computer science, engineering, biomedical informatics, neuroscience, psychology, data science, sociology, and various clinical specialties. Many teams combined technical skills in AI/ML with domain knowledge in neuroscience, aging, or healthcare.

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