Analytics Vidhya

FEBRUARY 21, 2022

This article was published as a part of the Data Science Blogathon. Image designed by the author – Shanthababu Introduction Every ML Engineer and Data Scientist must understand the significance of “Hyperparameter Tuning (HPs-T)” while selecting your right machine/deep learning model and improving the performance of the model(s).

ML Engineer 337

ML Engineer Data Scientist Deep Learning Data Science 337

Towards AI

APRIL 10, 2024

How much machine learning really is in ML Engineering? There are so many different data- and machine-learning-related jobs. But what actually are the differences between a Data Engineer, Data Scientist, ML Engineer, Research Engineer, Research Scientist, or an Applied Scientist?!

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ML Engineer ML Explainability Machine Learning 111

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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Data Scientist Machine Learning ML Engineer Actionable Intelligence 306

IBM Journey to AI blog

AUGUST 11, 2023

Both computer scientists and business leaders have taken note of the potential of the data. Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. MLOps is the next evolution of data analysis and deep learning. What is MLOps?

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Data Science DevOps Machine Learning Data Scientist 170

Towards AI

AUGUST 7, 2024

From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams Photo by Parabol | The Agile Meeting Toolbox on Unsplash In this article, we will explore the essential VS Code extensions that enhance productivity and collaboration for data scientists and machine learning (ML) engineers.

Data Science 116

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Towards AI

JULY 2, 2024

What are the most important skills for an ML Engineer? Well, I asked ML engineers at all these companies to share what they consider the top skills… And I’m telling you, there were a lot of answers I received and I bet you didn’t even think of many of them!

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Unite.AI

FEBRUARY 11, 2025

Nikhil Pareek, a former AI founder with multiple patents and research papers, has worked on autonomous drones and data science challenges for Fortune 50 companies. Charu Gupta, a revenue growth expert, has led multiple startups from inception to scaling revenues up to $100 million.

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Auto-complete ML Engineer AI AI 147

Marktechpost

OCTOBER 10, 2024

In today’s tech-driven world, data science and machine learning are often used interchangeably. This article explores the differences between data science vs. machine learning , highlighting their key functions, roles, and applications. What is Data Science? However, they represent distinct fields.

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Data Science Machine Learning Data Scientist ML Engineer 106

Towards AI

MARCH 14, 2024

How do you best learn Data Science and then get a Job? What is data science??? All the way back in 2012, Harvard Business Review said that Data Science was the sexiest job of the 21st century and recently followed up with an updated version of their article. How long does it take, and how much does it cost?

Data Science 105

Data Science ML Engineer Data Scientist ML 105

AWS Machine Learning Blog

OCTOBER 22, 2024

Amazon SageMaker is a cloud-based machine learning (ML) platform within the AWS ecosystem that offers developers a seamless and convenient way to build, train, and deploy ML models. He focuses on architecting and implementing large-scale generative AI and classic ML pipeline solutions.

ML Engineer 110

ML Engineer Data Scientist Machine Learning ML 110

AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative AI models have further sped up the need of ML adoption across industries.

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ML Data Scientist ML Engineer Data Science 128

Flipboard

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. Data scientists and ML engineers require capable tooling and sufficient compute for their work. Data scientists and ML engineers require capable tooling and sufficient compute for their work.

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ML DevOps Data Scientist ML Engineer 149

AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

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IBM Journey to AI blog

AUGUST 12, 2024

Instead, businesses tend to rely on advanced tools and strategies—namely artificial intelligence for IT operations (AIOps) and machine learning operations (MLOps)—to turn vast quantities of data into actionable insights that can improve IT decision-making and ultimately, the bottom line.

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Marktechpost

NOVEMBER 16, 2024

Generative AI for Data Scientists Specialization This specialization by IBM is designed for data professionals to learn generative AI, including prompt engineering and applying AI tools in data science. It features hands-on projects like text, image, and code generation, as well as creating prediction models.

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Artificial Intelligence Artificial Intelligence Prompt Engineer Prompt Engineering 103

ODSC - Open Data Science

FEBRUARY 2, 2023

Here’s what we found for both skills and platforms that are in demand for data scientist jobs. Data Science Skills and Competencies Aside from knowing particular frameworks and languages, there are various topics and competencies that any data scientist should know. Joking aside, this does infer particular skills.

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Data Science Data Scientist Big Data Machine Learning 98

Analytics Vidhya

FEBRUARY 17, 2022

This article was published as a part of the Data Science Blogathon. Image designed by the author Introduction Guys! Before getting started, just […]. The post K-Fold Cross Validation Technique and its Essentials appeared first on Analytics Vidhya.

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Data Science ML Engineer ML Python 343

AWS Machine Learning Blog

OCTOBER 1, 2024

Over the last 18 months, AWS has announced more than twice as many machine learning (ML) and generative artificial intelligence (AI) features into general availability than the other major cloud providers combined. These services play a pivotal role in addressing diverse customer needs across the generative AI journey.

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AWS Machine Learning Blog

APRIL 26, 2023

Do you need help to move your organization’s Machine Learning (ML) journey from pilot to production? Most executives think ML can apply to any business decision, but on average only half of the ML projects make it to production. Challenges Customers may face several challenges when implementing machine learning (ML) solutions.

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AWS Machine Learning Blog

JANUARY 23, 2025

The solution described in this post is geared towards machine learning (ML) engineers and platform teams who are often responsible for managing and standardizing custom environments at scale across an organization. This approach helps you achieve machine learning (ML) governance, scalability, and standardization.

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AWS Machine Learning Blog

OCTOBER 28, 2024

Real-world applications vary in inference requirements for their artificial intelligence and machine learning (AI/ML) solutions to optimize performance and reduce costs. SageMaker Model Monitor monitors the quality of SageMaker ML models in production. Your client applications invoke this endpoint to get inferences from the model.

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ML Metadata Data Scientist DevOps 107

Unite.AI

JUNE 19, 2024

In world of Artificial Intelligence (AI) and Machine Learning (ML), a new professionals has emerged, bridging the gap between cutting-edge algorithms and real-world deployment. Meet the MLOps Engineer: the orchestrating the seamless integration of ML models into production environments, ensuring scalability, reliability, and efficiency.

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Software Engineer DevOps Machine Learning ML 182

AWS Machine Learning Blog

SEPTEMBER 20, 2023

In these scenarios, as you start to embrace generative AI, large language models (LLMs) and machine learning (ML) technologies as a core part of your business, you may be looking for options to take advantage of AWS AI and ML capabilities outside of AWS in a multicloud environment.

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ODSC - Open Data Science

MARCH 10, 2025

AI and data science are advancing at a lightning-fast pace with new skills and applications popping up left and right. With real-world examples from regulated industries, this session equips data scientists, ML engineers, and risk professionals with the skills to build more transparent and accountable AIsystems.

Data Scientist 52

Data Scientist Data Science LLM Machine Learning 52

Unite.AI

FEBRUARY 12, 2025

The AI/ML engine built into MachineMetrics analyzes this machine data to detect anomalies and patterns that might indicate emerging problems. The platforms strength lies in its powerful data processing pipeline that cleans and contextualizes plant floor data in real-time, making it analysis-ready.

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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

JULY 8, 2024

As industries begin adopting processes dependent on machine learning (ML) technologies, it is critical to establish machine learning operations (MLOps) that scale to support growth and utilization of this technology. There were noticeable challenges when running ML workflows in the cloud.

Data Scientist 117

Data Scientist ML Engineer Machine Learning Data Science 117

ODSC - Open Data Science

FEBRUARY 9, 2023

It is often too much to ask for the data scientist to become a domain expert. However, in all cases the data scientist must develop strong domain empathy to help define and solve the right problems. Nina Zumel and John Mount, Practical Data Science with R, 2nd Ed.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts.

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AWS Machine Learning Blog

FEBRUARY 19, 2025

In this post, we provide best practices to maximize the value of SageMaker HyperPod task governance and make the administration and data science experiences seamless. Access control When working with SageMaker HyperPod task governance, data scientists will assume their specific role.

Data Scientist 74

Data Scientist Data Science ML Engineer Generative AI 74

Towards AI

FEBRUARY 9, 2025

Lets understand the most useful linear feature scaling techniques of Machine Learning (ML) in detail! Source: Image by NIR HIMI on Unsplash Machine Learning (ML) is a very vast field & requires a proper approach to formulate the solution for every problem, irrespective of the solution or problem being small scale or large scale.

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Machine Learning ML Engineer ML AI 67

ODSC - Open Data Science

APRIL 1, 2025

As Professor Lius talk makes clear, this isnt just an academic curiosityits a new foundation for solving problems that impact lives, environments, and economies.

BERT 52

BERT ML Engineer Data Science Deep Learning 52

AWS Machine Learning Blog

FEBRUARY 7, 2025

Data science teams often face challenges when transitioning models from the development environment to production. This post, part of the Governing the ML lifecycle at scale series ( Part 1 , Part 2 , Part 3 ), explains how to set up and govern a multi-account ML platform that addresses these challenges.

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ML Data Scientist ML Engineer Data Science 63

ODSC - Open Data Science

SEPTEMBER 21, 2023

Secondly, to be a successful ML engineer in the real world, you cannot just understand the technology; you must understand the business. Some typical examples are given in the following table, along with some discussion as to whether or not ML would be an appropriate tool for solving the problem: Figure 1.1:

Machine Learning 98

Machine Learning ML Engineer ML Data Science 98

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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AWS Machine Learning Blog

SEPTEMBER 23, 2024

Machine learning (ML) projects are inherently complex, involving multiple intricate steps—from data collection and preprocessing to model building, deployment, and maintenance. To start our ML project predicting the probability of readmission for diabetes patients, you need to download the Diabetes 130-US hospitals dataset.

ML 86

ML Computer Vision Data Scientist Machine Learning 86

AWS Machine Learning Blog

FEBRUARY 27, 2024

In this post, we share how Axfood, a large Swedish food retailer, improved operations and scalability of their existing artificial intelligence (AI) and machine learning (ML) operations by prototyping in close collaboration with AWS experts and using Amazon SageMaker.

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Machine Learning DevOps Data Scientist Data Quality 136