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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Big Data DevOps Automation Machine Learning 266

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.

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ML Engineer Data Scientist Machine Learning ML 113

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 152

AI News

MARCH 8, 2024

A job listing for an “Embodied Robotics Engineer” sheds light on the project’s goals, which include “designing, building, and maintaining open-source and low cost robotic systems that integrate AI technologies, specifically in deep learning and embodied AI.”

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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.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Data exploration and model development were conducted using well-known machine learning (ML) tools such as Jupyter or Apache Zeppelin notebooks. To address the legacy data science environment challenges, Rocket decided to migrate its ML workloads to the Amazon SageMaker AI suite.

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Data Science Data Scientist Data Ingestion DevOps 78

IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

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Data Science DevOps Machine Learning Data Scientist 170

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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Marktechpost

SEPTEMBER 25, 2024

With the rapid advancement of technology, surpassing human abilities in tasks like image classification and language processing, evaluating the energy impact of ML is essential. Historically, ML projects prioritized accuracy over energy efficiency, contributing to increased energy consumption.

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Machine Learning ML Software Engineer ML Engineer 103

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. As businesses across industries increasingly embrace AI and ML to gain a competitive edge, the demand for MLOps Engineers has skyrocketed.

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Software Engineer DevOps Machine Learning ML 182

AWS Machine Learning Blog

FEBRUARY 11, 2025

Get started with SageMaker JumpStart SageMaker JumpStart is a machine learning (ML) hub that can help accelerate your ML journey. Marc Karp is an ML Architect with the Amazon SageMaker Service team. He focuses on helping customers design, deploy, and manage ML workloads at scale.

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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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Marktechpost

OCTOBER 12, 2024

Machine Learning (ML) models have shown promising results in various coding tasks, but there remains a gap in effectively benchmarking AI agents’ capabilities in ML engineering. MLE-bench is a novel benchmark aimed at evaluating how well AI agents can perform end-to-end machine learning engineering.

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Machine Learning OpenAI ML Engineer ML 111

AWS Machine Learning Blog

FEBRUARY 19, 2025

In this example, the ML engineering team is borrowing 5 GPUs for their training task With SageMaker HyperPod, you can additionally set up observability tools of your choice. In our public workshop, we have steps on how to set up Amazon Managed Prometheus and Grafana dashboards.

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Data Scientist Data Science ML Engineer Generative AI 78

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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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. The top industries seeking AI engineers are technology, healthcare, gaming, finance, retail, national security, etc.

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AI Engineer Software Engineer Artificial Intelligence Artificial Intelligence 111

AWS Machine Learning Blog

DECEMBER 19, 2023

Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production at scale is challenging and requires a set of best practices.

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Machine Learning ML Engineer DevOps ML 132

Marktechpost

OCTOBER 10, 2024

Machine learning (ML) is a subset of artificial intelligence (AI) that builds algorithms capable of learning from data. Unlike traditional programming, where rules are explicitly defined, ML models learn patterns from data and make predictions or decisions autonomously. What is Machine Learning? fraud detection).

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Data Science Machine Learning Data Scientist ML Engineer 106

Towards AI

JANUARY 6, 2025

TOP 20 AI CERTIFICATIONS TO ENROLL IN 2025 Ramp up your AI career with the most trusted AI certification programs and the latest artificial intelligence skills. AGI would mean AI can think, learn, and work just like a human, an incredible leap in artificial intelligence technology.

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Towards AI

FEBRUARY 11, 2025

🚀 MLflow Experiment Tracking: The Ultimate Beginners Guide to Streamlining ML Workflows Photo by Alvaro Reyes on Unsplash Introduction Have you ever felt that you were losing command over your machine-learning projects? These obstacles can hinder your advancement and cause ML workflows to seem like an endless labyrinth.

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ML Machine Learning Data Scientist ML Engineer 67

AWS Machine Learning Blog

FEBRUARY 21, 2025

For this post, we have two active directory groups, ml-engineers and security-engineers. We test the access of two users, John Doe and Jane Smith, who are users of the ml-engineers group and security-engineers group, respectively. The secret name for John Doe is jdoe , and for Jane Smith, its jsmith.

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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. In this post, we walk through how to discover, deploy, and use the Pixtral 12B model for a variety of real-world vision use cases.

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ML Generative AI Computer Vision ML Engineer 103

ODSC - Open Data Science

FEBRUARY 9, 2023

That responsibility usually falls in the hands of a role called Machine Learning (ML) Engineer. Having empathy for your ML Engineering colleagues means helping them meet operational constraints. To continue with this analogy, you might think of the ML Engineer as the data scientist’s “editor.”

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Data Scientist Machine Learning ML Engineer ML 105

Towards AI

AUGUST 25, 2023

As a reminder, I highly recommend that you refer to more than one resource (other than documentation) when learning ML, preferably a textbook geared toward your learning level (beginner/intermediate / advanced). In a nutshell, AI Engineering is the application of software engineering best practices to the field of AI.

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Machine Learning Software Engineer Neural Network Data Science 98

AWS Machine Learning Blog

FEBRUARY 13, 2024

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts.

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ML Machine Learning ML Engineer Data Scientist 128

Pickl AI

JANUARY 29, 2024

2024 Tech breakdown: Understanding Data Science vs ML vs AI Quoting Eric Schmidt , the former CEO of Google, ‘There were 5 exabytes of information created between the dawn of civilisation through 2003, but that much information is now created every two days.’ AI comprises Natural Language Processing, computer vision, and robotics.

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Data Science ML Machine Learning Artificial Intelligence 52

Unite.AI

NOVEMBER 10, 2023

Artificial intelligence keeps booming, and if it continues permeating into every industry, it will completely transform the way we live. The basic idea is that these tools can be integrated by business developers (not ML specialists), which will allow us to quickly test the hypothesis of whether AI brings the expected effect or not.

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ODSC - Open Data Science

MARCH 10, 2025

Building Multimodal AI Agents: Agentic RAG with Vision-Language Models Suman Debnath, Principal AI/ML Advocate at Amazon WebServices Building a truly intelligent AI assistant requires overcoming the limitations of native Retrieval-Augmented Generation (RAG) models, especially when handling diverse data types like text, tables, and images.

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Data Scientist Data Science LLM Machine Learning 52

Towards AI

JANUARY 28, 2025

Photo by Markus Winkler on Unsplash You might have wandered the internet for a complete roadmap to learn ML. You might have been flooded with tons of courses like Learn Machine Learning in 3 monthsMachine Learning SimplifiedLearn ML in 1 weekand there are several others like these. Ill provide some resources to learn stuff.

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Machine Learning ML Engineer ML AI 54

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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Neural Network Software Engineer Algorithm Machine Learning 98

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. This is a guest post written by Axfood AB.

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Machine Learning DevOps Data Scientist Data Quality 137

AWS Machine Learning Blog

NOVEMBER 16, 2023

One of the key drivers of Philips’ innovation strategy is artificial intelligence (AI), which enables the creation of smart and personalized products and services that can improve health outcomes, enhance customer experience, and optimize operational efficiency.

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Data Scientist ML Data Science Automation 124

AWS Machine Learning Blog

MARCH 22, 2024

The AI Content Generator powered by Amazon Bedrock is an app available on the Contentful Marketplace that allows users to create, rewrite, summarize, and translate content using cutting-edge generative artificial intelligence (AI) models available and accessible through Amazon Bedrock in a simple and secure manner.

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Large Language Models Natural Language Processing NLP Software Engineer 122

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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Data Science Machine Learning Data Scientist Generative AI 97

AWS Machine Learning Blog

JUNE 19, 2024

Get ready to unlock the power of generative artificial intelligence (AI) and bring it directly into your Slack workspace. About the Authors Rushabh Lokhande is a Senior Data & ML Engineer with AWS Professional Services Analytics Practice.

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ML Engineer Generative AI Big Data ML 106

AWS Machine Learning Blog

FEBRUARY 12, 2025

About the authors Daniel Zagyva is a Senior ML Engineer at AWS Professional Services. As a next step, you can explore fine-tuning your own LLM with Medusa heads on your own dataset and benchmark the results for your specific use case, using the provided GitHub repository.

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LLM ML Natural Language Processing Machine Learning 77

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:

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Machine Learning ML Engineer ML Data Science 98