Marktechpost

AUGUST 8, 2023

In the ever-evolving landscape of machine learning, feature management has emerged as a key pain point for ML Engineers at Airbnb. Chronon empowers ML practitioners to define features and centralize data computation for model training and production inference, guaranteeing accuracy and consistency throughout the process.

Machine Learning 98

Machine Learning ML Engineer Data Ingestion ML 98

The MLOps Blog

JUNE 13, 2024

Data scientists often lack focus, time, or knowledge about software engineering principles. As a result, poor code quality and reliance on manual workflows are two of the main issues in ML development processes. I started as a full-stack developer but have gradually moved toward data and ML engineering.

ML 59

ML Data Scientist Automation Software Development 59

O'Reilly Media

OCTOBER 19, 2021

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. What does a modern technology stack for streamlined ML processes look like?

DevOps 145

DevOps Software Engineer Data Scientist ML 145

ODSC - Open Data Science

SEPTEMBER 21, 2023

Yes, these things are part of any job in technology, and they can definitely be super fun, but you have to be strategic about how you spend your time and always be aware of your value proposition. Secondly, to be a successful ML engineer in the real world, you cannot just understand the technology; you must understand the business.

Machine Learning 98

Machine Learning ML Engineer ML Data Science 98

Snorkel AI

MARCH 18, 2025

Its neither practical nor effective, and it is most definitely frustrating. Without actionable insights, AI teams are more or less asked to throw spaghetti on the wall and see what sticks.

ML Engineer 52

ML Engineer LLM AI AI 52

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.

Machine Learning 129

Machine Learning DevOps Data Scientist Data Quality 129

AWS Machine Learning Blog

FEBRUARY 12, 2025

For this post, we use a dataset called sql-create-context , which contains samples of natural language instructions, schema definitions and the corresponding SQL query. We encourage you to read this post while running the code in the notebook.

LLM 75

LLM ML Natural Language Processing Machine Learning 75

O'Reilly Media

JANUARY 17, 2023

This mindset has followed me into my work in ML/AI. Because if companies use code to automate business rules, they use ML/AI to automate decisions. Given that, what would you say is the job of a data scientist (or ML engineer, or any other such title)? But first, let’s talk about the typical ML workflow.

Automation 145

Automation Robotics Data Scientist ML 145

ODSC - Open Data Science

FEBRUARY 2, 2023

Much of what we found was to be expected, though there were definitely a few surprises. Machine Learning As machine learning is one of the most notable disciplines under data science, most employers are looking to build a team to work on ML fundamentals like algorithms, automation, and so on.

Data Science 98

Data Science Data Scientist Big Data Machine Learning 98

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.

Machine Learning 98

Machine Learning Software Engineer Neural Network Data Science 98

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.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

AWS Machine Learning Blog

APRIL 29, 2024

For AWS and Outerbounds customers, the goal is to build a differentiated machine learning and artificial intelligence (ML/AI) system and reliably improve it over time. Second, open source Metaflow provides the necessary software infrastructure to build production-grade ML/AI systems in a developer-friendly manner.

ML 116

ML Python Data Scientist Machine Learning 116

AWS Machine Learning Blog

AUGUST 22, 2024

You can use Amazon SageMaker Model Building Pipelines to collaborate between multiple AI/ML teams. SageMaker Pipelines You can use SageMaker Pipelines to define and orchestrate the various steps involved in the ML lifecycle, such as data preprocessing, model training, evaluation, and deployment.

Generative AI 114

Generative AI Metadata Python ML 114

AWS Machine Learning Blog

SEPTEMBER 18, 2023

Machine learning (ML) is becoming increasingly complex as customers try to solve more and more challenging problems. This complexity often leads to the need for distributed ML, where multiple machines are used to train a single model. SageMaker is a fully managed service for building, training, and deploying ML models.

Machine Learning 118

Machine Learning ML Python Auto-complete 118

The MLOps Blog

OCTOBER 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. And later, an MLOps engineer.

ML 52

ML Data Scientist Machine Learning Data Science 52

The MLOps Blog

AUGUST 4, 2023

Situations described above arise way too often in ML teams, and their consequences vary from a single developer’s annoyance to the team’s inability to ship their code as needed. Let’s dive into the world of monorepos, an architecture widely adopted in major tech companies like Google, and how they can enhance your ML workflows.

ML 52

ML Machine Learning Python Software Engineer 52

Pickl AI

APRIL 19, 2023

Different industries from education, healthcare to marketing, retail and ecommerce require Machine Learning Engineers. Job market will experience a rise of 13% by 2026 for ML Engineers Why is Machine Learning Important? Accordingly, an entry-level ML engineer will earn around 5.1 Consequently.

Machine Learning 52

Machine Learning ML Engineer Data Scientist ML 52

AWS Machine Learning Blog

AUGUST 20, 2024

About the Authors Sundar Raghavan is an AI/ML Specialist Solutions Architect at AWS, helping customers build scalable and cost-efficient AI/ML pipelines with Human in the Loop services. Jacky Shum is a Software Engineer at AWS in the SageMaker Ground Truth team.

Software Engineer 102

Software Engineer ML Machine Learning Metadata 102

The MLOps Blog

AUGUST 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. Stefan: Yeah.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

AWS Machine Learning Blog

SEPTEMBER 1, 2023

ML operationalization summary As defined in the post MLOps foundation roadmap for enterprises with Amazon SageMaker , ML and operations (MLOps) is the combination of people, processes, and technology to productionize machine learning (ML) solutions efficiently.

Generative AI 120

Generative AI Prompt Engineering Prompt Engineer ML 120

Chatbots Life

MAY 12, 2023

We will discuss how models such as ChatGPT will affect the work of software engineers and ML engineers. Will ChatGPT replace software engineers? Will ChatGPT replace ML Engineers? Although the model acts as a highly-skilled, the profession definitely carries a lot of risks. What is ChatGPT capable of?

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ChatGPT Software Engineer NLP ML Engineer 90

AWS Machine Learning Blog

MAY 13, 2024

We also explore the utility of the RAG prompt engineering technique as it applies to the task of summarization. Evaluating LLMs is an undervalued part of the machine learning (ML) pipeline. Embeddings are numerical representations of real-world objects that ML systems use to understand complex knowledge domains like humans do.

Generative AI 123

Generative AI Prompt Engineering Prompt Engineer LLM 123

AWS Machine Learning Blog

OCTOBER 15, 2024

HD – Optimized for high-definition, Bria 2.2 HD offers high-definition visual content that meets the demanding needs of high-resolution applications, making sure every detail is crisp and clear. About the Authors Bar Fingerman is the Head of AI/ML Engineering at Bria. Fast – Optimized for speed, Bria 2.3 and Bria 2.2

Generative AI 77

Generative AI ML Python Responsible AI 77

AWS Machine Learning Blog

OCTOBER 22, 2024

Data scientists and machine learning (ML) engineers use pipelines for tasks such as continuous fine-tuning of large language models (LLMs) and scheduled notebook job workflows. Create a complete AI/ML pipeline for fine-tuning an LLM using drag-and-drop functionality. Brock Wade is a Software Engineer for Amazon SageMaker.

Automation 79

Automation LLM DevOps Python 79

The MLOps Blog

JANUARY 23, 2023

Machine Learning Operations (MLOps): Overview, Definition, and Architecture” By Dominik Kreuzberger, Niklas Kühl, Sebastian Hirschl Great stuff. If you haven’t read it yet, definitely do so. Came to ML from software. I don’t see what special role ML and MLOps engineers would play here. –

DevOps 59

DevOps Metadata Software Engineer Data Scientist 59

ODSC - Open Data Science

JULY 19, 2023

Machine Learning Operations (MLOps) can significantly accelerate how data scientists and ML engineers meet organizational needs. A well-implemented MLOps process not only expedites the transition from testing to production but also offers ownership, lineage, and historical data about ML artifacts used within the team.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52

AWS Machine Learning Blog

NOVEMBER 9, 2023

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance.

Data Drift 116

Data Drift Auto-complete ML Automation 116

Snorkel AI

MARCH 18, 2025

Its neither practical nor effective, and it is most definitely frustrating. Without actionable insights, AI teams are more or less asked to throw spaghetti on the wall and see what sticks.

ML Engineer 52

ML Engineer LLM AI AI 52

AWS Machine Learning Blog

AUGUST 1, 2023

Artificial intelligence (AI) and machine learning (ML) models have shown great promise in addressing these challenges. Amazon SageMaker , a fully managed ML service, provides an ideal platform for hosting and implementing various AI/ML-based summarization models and approaches. No ML engineering experience required.

ML 83

ML Large Language Models NLP Machine Learning 83

Mlearning.ai

FEBRUARY 9, 2023

11 key differences in 2023 Photo by Jan Tinneberg on Unsplash Working in Data Science and Machine Learning (ML) professions can be a lot different from the expectation of it. I started working in Data Science right after graduating with an MS degree in Electrical and Computer Engineering from the University of California, Los Angeles (UCLA).

Data Scientist 52

Data Scientist Data Science ML Machine Learning 52

TheSequence

MAY 24, 2023

I originally did a master's degree in physics focusing on astrophysics, but around that time, I noticed the breakthroughs happening in ML so I decided to switch the focus of my studies towards ML. Were there any research breakthroughs in StarCoder, or would you say it was more of a crafty ML engineering effort?

Auto-complete 59

Auto-complete ML Python Machine Learning 59

AWS Machine Learning Blog

JUNE 13, 2023

This post is co-written with Jad Chamoun, Director of Engineering at Forethought Technologies, Inc. and Salina Wu, Senior ML Engineer at Forethought Technologies, Inc. The main challenges were integrating a preprocessing step and accommodating two model artifacts per model definition.

Generative AI 73

Generative AI Auto-complete AI Modeling Machine Learning 73

AWS Machine Learning Blog

JUNE 8, 2023

This enables you to begin machine learning (ML) quickly. A SageMaker real-time inference endpoint enables fast, scalable deployment of ML models for predicting events. Victor Rojo is a highly experienced technologist who is passionate about the latest in AI, ML, and software development.

Generative AI 83

Generative AI LLM Machine Learning Large Language Models 83

Snorkel AI

OCTOBER 12, 2023

Discover the strategies used to drive data-driven decisions within the complex governmental landscape and gain valuable perspectives on the future of AI/ML, the ethical considerations in data science, and the transformative potential of leveraging data to better society. Current specialized ML libraries (e.g.,

Data Scientist 64

Data Scientist ML Computer Vision AI 64

Snorkel AI

OCTOBER 12, 2023

Discover the strategies used to drive data-driven decisions within the complex governmental landscape and gain valuable perspectives on the future of AI/ML, the ethical considerations in data science, and the transformative potential of leveraging data to better society. Current specialized ML libraries (e.g.,

Data Scientist 59

Data Scientist ML Computer Vision AI 59

Snorkel AI

JULY 5, 2023

Abhishek Ratna, in AI ML marketing, and TensorFlow developer engineer Robert Crowe, both from Google, spoke as part of a panel entitled “Practical Paths to Data-Centricity in Applied AI” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Robert, I will leave the introduction part to you. AR : Absolutely.

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

Snorkel AI

JULY 5, 2023

Abhishek Ratna, in AI ML marketing, and TensorFlow developer engineer Robert Crowe, both from Google, spoke as part of a panel entitled “Practical Paths to Data-Centricity in Applied AI” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Robert, I will leave the introduction part to you. AR : Absolutely.

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52