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

ODSC - Open Data Science

FEBRUARY 2, 2023

Much of what we found was to be expected, though there were definitely a few surprises. Cloud Engineering Most data science is done on the cloud now, as teams will be working together to analyze large datasets consistently across the team. This will be a major theme moving forward, and is something definitely not seen 10 years ago.

Data Science 98

Data Science Data Scientist Big Data Machine Learning 98

AWS Machine Learning Blog

FEBRUARY 27, 2024

The SageMaker project template includes seed code corresponding to each step of the build and deploy pipelines (we discuss these steps in more detail later in this post) as well as the pipeline definition—the recipe for how the steps should be run. Pavel Maslov is a Senior DevOps and ML engineer in the Analytic Platforms team.

Machine Learning 135

Machine Learning DevOps Data Scientist Data Quality 135

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?

ChatGPT 90

ChatGPT Software Engineer NLP ML Engineer 90

Towards AI

AUGUST 25, 2023

In graduate school, a course in AI will usually have a quick review of the core ML concepts (covered in a previous course) and then cover searching algorithms, game theory, Bayesian Networks, Markov Decision Processes (MDP), reinforcement learning, and more. Any competent software engineer can implement any algorithm.

Machine Learning 98

Machine Learning Software Engineer Neural Network Data Science 98

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

Abhinay Sandeboina is a Engineering Manager at AWS Human In The Loop (HIL). He has been in AWS for over 2 years and his teams are responsible for managing ML platform services. He has a decade of experience in software/ML engineering building infrastructure platforms at scale.

Software Engineer 110

Software Engineer ML Machine Learning Metadata 110

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. The new category is often called MLOps.

DevOps 145

DevOps Software Engineer Data Scientist ML 145

AWS Machine Learning Blog

APRIL 29, 2024

Metaflow overview Metaflow was originally developed at Netflix to enable data scientists and ML engineers to build ML/AI systems quickly and deploy them on production-grade infrastructure. How Metaflow integrates with Trainium From a Metaflow developer perspective, using Trainium is similar to other accelerators.

ML 124

ML Python Data Scientist Machine Learning 124

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

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. About the authors Daniel Zagyva is a Senior ML Engineer at AWS Professional Services. We encourage you to read this post while running the code in the notebook.

LLM 78

LLM ML Natural Language Processing Machine Learning 78

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. Download the pipeline definition as a JSON file to your local environment by choosing Export at the bottom of the visual editor.

Automation 85

Automation LLM DevOps Python 85

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

Generative AI 83

Generative AI ML Python Responsible AI 83

AWS Machine Learning Blog

SEPTEMBER 18, 2023

ML engineers must handle parallelization, scheduling, faults, and retries manually, requiring complex infrastructure code. In this post, we discuss the benefits of using Ray and Amazon SageMaker for distributed ML, and provide a step-by-step guide on how to use these frameworks to build and deploy a scalable ML workflow.

Machine Learning 126

Machine Learning ML Python Auto-complete 126

AWS Machine Learning Blog

SEPTEMBER 20, 2023

This approach is beneficial if you use AWS services for ML for its most comprehensive set of features, yet you need to run your model in another cloud provider in one of the situations we’ve discussed. Key concepts Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning. device), target.to(device)

ML 126

ML Python Deep Learning Machine Learning 126

AWS Machine Learning Blog

AUGUST 22, 2024

In the notebook, we already added the @step decorator at the beginning of each function definition in the cell where the function was defined, as shown in the following code. Data scientists, ML engineers, IT staff, and DevOps teams must work together to operationalize models from research to deployment and maintenance.

Generative AI 123

Generative AI Metadata Python ML 123

AWS Machine Learning Blog

MAY 13, 2024

For more details on the definition of various forms of this score, please refer to part 1 of this blog. His expertise is in reproducible and end-to-end AI/ML methods, practical implementations, and helping global healthcare customers formulate and develop scalable solutions to interdisciplinary problems.

Generative AI 131

Generative AI Prompt Engineer Prompt Engineering LLM 131

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

SEPTEMBER 1, 2023

After the completion of the research phase, the data scientists need to collaborate with ML engineers to create automations for building (ML pipelines) and deploying models into production using CI/CD pipelines. Only prompt engineering is necessary for better results.

Generative AI 126

Generative AI Prompt Engineering Prompt Engineer ML 126

AWS Machine Learning Blog

FEBRUARY 12, 2024

Package model for inference – Using a processing job, if the evaluation results are positive, the model is packaged, stored in Amazon S3, and made ready for upload to the internal ML portal. Explain – SageMaker Clarify generates an explainability report. Two distinct repositories are used.

ML 133

ML Explainability Machine Learning Deep Learning 133

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. How about the ML engineer? MLOps engineer today is either an ML engineer (building ML-specific software) or a DevOps engineer.

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

AUGUST 1, 2023

To start working with a model to learn about the capabilities of ML, all you need to do is open SageMaker Studio, find a pre-trained model you want to use in the Hugging Face Model Hub , and choose SageMaker as your deployment method. No ML engineering experience required. It’s as easy as that!

ML 91

ML Large Language Models NLP Machine Learning 91

The MLOps Blog

JUNE 13, 2024

I started as a full-stack developer but have gradually moved toward data and ML engineering. My current role is MLOps engineer at Arbetsförmedlingen , Sweden’s largest employment agency. As ML engineers, we’re often very enthusiastic about MLOps and the automation of practically everything.

ML 59

ML Data Scientist Automation Software Development 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 81

Generative AI Auto-complete AI Modeling Machine Learning 81

Pickl AI

JANUARY 29, 2024

Data Science Vs Machine Learning Vs AI Aspect Data Science Artificial Intelligence Machine Learning Definition Data Science is the field that deals with the extraction of knowledge and insights from data through various processes. AI Engineer, Machine Learning Engineer, and Robotics Engineer are prominent roles in AI.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

TheSequence

MAY 24, 2023

Were there any research breakthroughs in StarCoder, or would you say it was more of a crafty ML engineering effort? Evaluation is definitely in its infancy compared to natural language and will need to improve to better capture the user experience. What are the biggest next milestones for coding LLMs?

Auto-complete 59

Auto-complete ML Python Machine Learning 59

AWS Machine Learning Blog

JUNE 8, 2023

Ryan Gomes is a Data & ML Engineer with the AWS Professional Services Intelligence Practice. Prompts function as a form of context that helps direct the model toward generating relevant responses. He leads the NYC machine learning and AI meetup. In his spare time, he enjoys offshore sailing and playing jazz.

Generative AI 90

Generative AI LLM Machine Learning Large Language Models 90

Mlearning.ai

FEBRUARY 9, 2023

Data Science is an umbrella role with common roles such as Data Analytics, research, ML model building, ML Ops, and ML engineering underneath. The definition of the role of a Data Scientist can be different between organizations and is usually dependent on the expectation of the company’s leadership.

Data Scientist 52

Data Scientist Data Science ML Machine Learning 52

AWS Machine Learning Blog

NOVEMBER 9, 2023

Under Advanced Project Options , for Definition , select Pipeline script from SCM. She is passionate about developing, deploying, and explaining AI/ ML solutions across various domains. Prior to this role, she led multiple initiatives as a data scientist and ML engineer with top global firms in the financial and retail space.

Data Drift 122

Data Drift Auto-complete ML Automation 122

Snorkel AI

JULY 5, 2023

RC : I have had ML engineers tell me, “You didn’t need to do feature selection anymore, and that you could just throw everything at the model and it will figure out what to keep and what to throw away.” That is definitely a problem. So does that mean feature selection is no longer necessary? And I can get us started here.

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

Snorkel AI

JULY 5, 2023

RC : I have had ML engineers tell me, “You didn’t need to do feature selection anymore, and that you could just throw everything at the model and it will figure out what to keep and what to throw away.” That is definitely a problem. So does that mean feature selection is no longer necessary? And I can get us started here.

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

Snorkel AI

JULY 5, 2023

RC : I have had ML engineers tell me, “You didn’t need to do feature selection anymore, and that you could just throw everything at the model and it will figure out what to keep and what to throw away.” That is definitely a problem. So does that mean feature selection is no longer necessary? And I can get us started here.

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

The MLOps Blog

AUGUST 3, 2023

This is Piotr Niedźwiedź and Aurimas Griciūnas from neptune.ai , and you’re listening to ML Platform Podcast. Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. I term it as a feature definition store. I also recently found out, you are the CEO of DAGWorks.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

The MLOps Blog

OCTOBER 3, 2023

Mikiko Bazeley: You definitely got the details correct. I joined FeatureForm last October, and before that, I was with Mailchimp on their ML platform team. I definitely don’t think I’m an influencer. I see so many of these job seekers, especially on the MLOps side or the ML engineer side.

ML 52

ML Data Scientist Machine Learning Data Science 52

ODSC - Open Data Science

JANUARY 3, 2025

Next, it provides a deep dive into the anatomy of an AI Agent, examining its definition, role, and practical applications, including how LLMs, memory, and tools work together. Cloning NotebookLM with Open Weights Models Niels Bantilan, Chief ML Engineer atUnion.AI

LLM 40

LLM AI AI Prompt Engineering 40

Snorkel AI

OCTOBER 12, 2023

In this session, Snorkel AI ML Engineer Ashwini Ramamoorthy explores how data-centric AI can be leveraged to simplify and streamline this process. To start, they highlight common but underrated challenges related to label schema definition, high cardinality, and multi-label problem formulations.

Data Scientist 64

Data Scientist ML Computer Vision AI 64