ODSC - Open Data Science

APRIL 28, 2023

Be sure to check out her talk, “ Power trusted AI/ML Outcomes with Data Integrity ,” there! Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation.

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Flipboard

SEPTEMBER 4, 2023

In a review published in Engineering, scientists explore the burgeoning field of machine learning (ML) and its applications in chemistry.

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Dataconomy

MAY 2, 2023

They design, develop, and deploy the machine learning algorithms that power everything from self-driving cars to personalized recommendations. They are the driving force behind the artificial intelligence revolution, creating new opportunities and possibilities that were once the stuff of science fiction. They build the future.

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Analytics Vidhya

JUNE 12, 2023

Introduction Meet Tajinder, a seasoned Senior Data Scientist and ML Engineer who has excelled in the rapidly evolving field of data science. Tajinder’s passion for unraveling hidden patterns in complex datasets has driven impactful outcomes, transforming raw data into actionable intelligence.

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Flipboard

FEBRUARY 14, 2025

Hemant Madaan, an expert in AI/ML and CEO of JumpGrowth, explores the ethical implications of advanced language models. Artificial intelligence (AI) has become a cornerstone of modern business operations, driving efficiencies and delivering insights across various sectors. However, as AI systems

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AWS Machine Learning Blog

MARCH 8, 2023

Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML models, and then directly deploy them into a production-ready hosted environment. Create a custom container image for ML model training and push it to Amazon ECR.

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AWS Machine Learning Blog

JANUARY 21, 2025

In this post, we show you how Amazon Web Services (AWS) helps in solving forecasting challenges by customizing machine learning (ML) models for forecasting. This visual, point-and-click interface democratizes ML so users can take advantage of the power of AI for various business applications. One of these methods is quantiles.

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Dataconomy

APRIL 3, 2025

in Computer Science and Engineering with a stellar GPA of 8.61, Harshit set a high bar for aspiring innovators. He re-architected big-data systems behind ML recommendation pipelines for using serverless architectures, ensuring privacy compliance for all datasets. During competitions, Harshit developed technology skills.

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Flipboard

MARCH 15, 2025

The accumulation of large datasets by the scientific community has surpassed the capacity of traditional processing methods, underscoring the critical need for innovative and efficient algorithms capable of navigating through extensive existing experimental data.

Machine Learning 138

Machine Learning Machine Learning ML ML 138

Dataconomy

APRIL 4, 2025

Understanding of AI, ML, and NLP A strong grasp of machine learning concepts, algorithms, and natural language processing is essential in this role. Skills and requirements for AI prompt engineers To succeed as an AI prompt engineer, individuals need a specific set of skills and knowledge bases.

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Flipboard

MAY 16, 2023

When we talk about artificial intelligence (AI) in business and society today, what we really mean is machine learning (ML). This refers to applications that use algorithms (a set of instructions) to become increasingly good at performing a particular task as it is exposed to more and more data …

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Towards AI

AUGUST 24, 2023

Common mistakes and misconceptions about learning AI/ML Markus Spiske on Unsplash A common misconception of beginners is that they can learn AI/ML from a few tutorials that implement the latest algorithms, so I thought I would share some notes and advice on learning AI. Trying to code ML algorithms from scratch.

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AI AI Algorithm ML 98

Dataversity

OCTOBER 18, 2022

While humans may be the most intellectual creations and sit atop the “food chain,” artificial intelligence (AI) is a branch of computer science that can simulate human intelligence in many cases. AI is implemented via machine learning (ML) and performs tasks traditionally executed by humans.

Machine Learning 98

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NYU Center for Data Science

AUGUST 29, 2024

Puli recently finished his PhD in Computer Science at NYU’s Courant Institute, advised by CDS Assistant Professor of Computer Science and Data Science Rajesh Ranganath. He is partly supported by the Apple Scholars in AI/ML PhD fellowship. Standard algorithms aren’t designed for this scenario.

Hypothesis Testing 72

Hypothesis Testing Computer Science Computer Science Data Science 72

AWS Machine Learning Blog

JUNE 9, 2023

a low-code enterprise graph machine learning (ML) framework to build, train, and deploy graph ML solutions on complex enterprise-scale graphs in days instead of months. With GraphStorm, we release the tools that Amazon uses internally to bring large-scale graph ML solutions to production. license on GitHub. GraphStorm 0.1

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Flipboard

MARCH 15, 2023

Artificial intelligence (AI) relies heavily on large, diverse and meticulously-labeled datasets to train machine learning (ML) algorithms. In the modern era, data has become the lifeblood of AI, and obtaining the right data is considered the most critical and challenging aspect of developing robust …

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ODSC - Open Data Science

FEBRUARY 2, 2023

Just as a writer needs to know core skills like sentence structure, grammar, and so on, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and so on. As MLOps become more relevant to ML demand for strong software architecture skills will increase as well.

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AWS Machine Learning Blog

MARCH 21, 2025

JupyterLab applications flexible and extensive interface can be used to configure and arrange machine learning (ML) workflows. million scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics.

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AWS AI AI Data Scientist 107

IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications.

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AWS Machine Learning Blog

JUNE 25, 2024

This solution simplifies the integration of advanced monitoring tools such as Prometheus and Grafana, enabling you to set up and manage your machine learning (ML) workflows with AWS AI Chips. By deploying the Neuron Monitor DaemonSet across EKS nodes, developers can collect and analyze performance metrics from ML workload pods.

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Flipboard

JANUARY 9, 2025

In this work, we present the method of Statistically Enhanced Learning (SEL), a formalization framework of existing feature engineering and extraction tasks in Machine Learning (ML). Contrary to existing approaches, predictors are not directly observed but obtained as statistical estimators.

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Algorithm Data Scientist Machine Learning Machine Learning 81

Towards AI

FEBRUARY 15, 2024

AI Engineers: Your Definitive Career Roadmap Become a professional certified AI engineer by enrolling in the best AI ML Engineer certifications that help you earn skills to get the highest-paying job. Coding, algorithms, statistics, and big data technologies are especially crucial for AI engineers.

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Towards AI

JANUARY 6, 2025

Professional certificate for computer science for AI by HARVARD UNIVERSITY Professional certificate for computer science for AI is a 5-month AI course that is inclusive of self-paced videos for participants; who are beginners or possess intermediate-level understanding of artificial intelligence.

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AWS Machine Learning Blog

JANUARY 31, 2025

Increasingly, FMs are completing tasks that were previously solved by supervised learning, which is a subset of machine learning (ML) that involves training algorithms using a labeled dataset. His passion is for solving challenging real-world computer vision problems and exploring new state-of-the-art methods to do so.

Supervised Learning 74

Supervised Learning AWS Data Scientist ML 74

Towards AI

AUGUST 16, 2023

In fact, AI/ML graduate textbooks do not provide a clear and consistent description of the AI software engineering process. Therefore, I thought it would be helpful to give a complete description of the AI engineering process or AI Process, which is described in most AI/ML textbooks [5][6]. 85% or more of AI projects fail [1][2].

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AI AI Machine Learning Machine Learning 98

Pickl AI

DECEMBER 26, 2024

Introduction In recent years, two technological fields have emerged as frontrunners in shaping the future: Artificial Intelligence (AI) and Quantum Computing. A study demonstrated that quantum algorithms could accelerate the discovery of new materials by up to 100 times compared to classical methods.

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Pickl AI

JANUARY 29, 2024

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. The collective strength of both forms the groundwork for AI and Data Science, propelling innovation.

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AWS Machine Learning Blog

DECEMBER 10, 2024

You can try this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms and models that can be deployed with one click for running inference. He holds a Bachelors degree in Computer Science and Bioinformatics. Specialist Solutions Architect working on generative AI.

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Flipboard

NOVEMBER 6, 2024

when cases with a small amount of free air (total volume <10 ml) are excluded. These findings suggest that the model can deliver accurate and consistent predictions for pneumoperitoneum in computed tomography scans with segmented masks, potentially accelerating diagnostic and treatment workflows in emergency care.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

Amazon SageMaker is a comprehensive, fully managed machine learning (ML) platform that revolutionizes the entire ML workflow. It offers an unparalleled suite of tools that cater to every stage of the ML lifecycle, from data preparation to model deployment and monitoring.

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AWS Machine Learning Blog

APRIL 7, 2025

This approach allows for greater flexibility and integration with existing AI and machine learning (AI/ML) workflows and pipelines. By providing multiple access points, SageMaker JumpStart helps you seamlessly incorporate pre-trained models into your AI/ML development efforts, regardless of your preferred interface or workflow.

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NYU Center for Data Science

NOVEMBER 15, 2023

Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce Harrop, Benjamin Hillman, Andrea Jenney, Savannah L.

Data Science 98

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Pickl AI

DECEMBER 25, 2024

Key Takeaways Business Analytics targets historical insights; Data Science excels in prediction and automation. Business Analytics requires business acumen; Data Science demands technical expertise in coding and ML. With added skills, professionals can shift between Business Analytics and Data Science.

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AWS Machine Learning Blog

DECEMBER 6, 2024

You can try these models with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms and models that can be deployed with one click for running inference. It provides a collection of pre-trained models that you can deploy quickly, accelerating the development and deployment of ML applications.

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NYU Center for Data Science

JULY 18, 2023

MaD & MaD+ The Math and Data (MaD) group is a collaboration between CDS and the NYU Courant Institute of Mathematical Sciences. ML² The Machine Learning for Language (ML²) group works on machine learning methods for natural language processing (NLP) through developing cutting-edge models and engaging in research.

Data Science 98

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AWS Machine Learning Blog

JANUARY 13, 2023

Machine learning (ML) presents an opportunity to address some of these concerns and is being adopted to advance data analytics and derive meaningful insights from diverse HCLS data for use cases like care delivery, clinical decision support, precision medicine, triage and diagnosis, and chronic care management.

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Towards AI

AUGUST 16, 2023

Pietro Jeng on Unsplash MLOps is a set of methods and techniques to deploy and maintain machine learning (ML) models in production reliably and efficiently. Many people use the term “pipeline” in MLOps which can be confusing since pipeline is computer science term that refers to a linear sequence with a single input/output.

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