Analytics Vidhya

OCTOBER 6, 2023

Ray streamlines complex tasks for ML engineers, data scientists, and developers. Python Ray is a dynamic framework revolutionizing distributed computing. Developed by UC Berkeley’s RISELab, it simplifies parallel and distributed Python applications.

Python 300

Python ML Engineer Data Scientist ML 300

Towards AI

FEBRUARY 21, 2023

A sensible proxy sub-question might then be: Can ChatGPT function as a competent machine learning engineer? The Set Up If ChatGPT is to function as an ML engineer, it is best to run an inventory of the tasks that the role entails. ChatGPT’s job as our ML engineer […]

ML Engineer 93

ML Engineer ML ChatGPT Computer Vision 93

Analytics Vidhya

JANUARY 28, 2022

Introduction A Machine Learning solution to an unambiguously defined business problem is developed by a Data Scientist ot ML Engineer. This article was published as a part of the Data Science Blogathon.

ML 284

ML ML Engineer Data Scientist Machine Learning 284

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.

Data Scientist 265

Data Scientist Machine Learning ML Engineer Actionable Intelligence 265

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.”

Robotics 271

Robotics Big Data Deep Learning Machine Learning 271

AI News

JULY 28, 2023

According to a recent report by Harnham , a leading data and analytics recruitment agency in the UK, the demand for ML engineering roles has been steadily rising over the past few years. AI and machine learning are reshaping the job landscape, with higher incentives being offered to attract and retain expertise amid talent shortages.

ML 211

ML ML Engineer Data Science Big Data 211

TheSequence

MARCH 8, 2024

VEW SPEAKER LINEUP Here’s a sneak peek of the agenda: LangChain Keynote: Hear from Lance Martin, an ML leader at LangChain, a leading orchestration framework for large language models (LLMs).

ML Engineer 52

ML Engineer ML Large Language Models Data Scientist 52

TheSequence

FEBRUARY 19, 2024

Diverse Expertise : Network with a wide array of AI and ML engineers, from seasoned veterans to those leading the charge at their companies, all eager to share their unique perspectives and knowledge. SAVE YOUR SPOT

ML Engineer 52

ML Engineer ML AI AI 52

Flipboard

DECEMBER 12, 2023

Whether you're a seasoned ML engineer or a new LLM developer, these tools will help you get more productive and accelerate the development and deployment of your AI projects.

LLM 165

LLM ML Engineer ML AI 165

TheSequence

NOVEMBER 3, 2023

Manager, ML Engineering at HelloFresh “Fireside Chat: LLMs, Real Time & Other Trends in the Production ML Space,” with Ali Ghodsi, CEO & Co-founder at Databricks , and Mike Del Balso, CEO & Co-founder at Tecton “Evolution of the Ads Ranking System at Pinterest,” by Aayush Mudgal, Sr.

ML Engineer 52

ML Engineer ML Software Engineer Data Scientist 52

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.

Machine Learning 116

Machine Learning OpenAI ML Engineer ML 116

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 113

Data Science ML ML Engineer Data Scientist 113

Flipboard

FEBRUARY 28, 2023

As a result, the AI production gap, the gap between “that’s neat” and “that’s useful,” has been much larger and more formidable than ML engineers first anticipated. Fortunately, as more and more ML engineers have embraced a data-centric approach to AI development, the implementation of active learning strategies have been on the rise.

Generative AI 132

Generative AI ML Engineer Computer Vision Robotics 132

AWS Machine Learning Blog

DECEMBER 4, 2024

Available in SageMaker AI and SageMaker Unified Studio (preview) Data scientists and ML engineers can access these applications from Amazon SageMaker AI (formerly known as Amazon SageMaker) and from SageMaker Unified Studio. Comet has been trusted by enterprise customers and academic teams since 2017.

ML 127

ML Generative AI Data Scientist ML Engineer 127

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.”

Data Scientist 105

Data Scientist Machine Learning ML Engineer ML 105

TheSequence

DECEMBER 1, 2023

At Flo Health, the maker of the most popular women’s health app in the world, ML is an engineering discipline — and as a quickly growing company, their ML team faces significant operational challenges, such as a disjointed approach to ML, with systems spread across the company.

ML Engineer 52

ML Engineer ML 52

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. JuMa is now available to all data scientists, ML engineers, and data analysts at BMW Group.

ML 153

ML DevOps Data Scientist ML Engineer 153

Unite.AI

JUNE 29, 2023

The Vertex AI platform has gained growing popularity among clients as it accelerates ML development, slashing production time by up to 80% compared to alternative methods. It offers an extensive suite of ML Ops capabilities, enabling ML engineers, data scientists, and developers to contribute efficiently.

Machine Learning 263

Machine Learning ML AI AI 263

Towards AI

MARCH 14, 2024

I mean, ML engineers often spend most of their time handling and understanding data. So, how is a data scientist different from an ML engineer? Well, there are three main reasons for this confusing overlap between the role of a data scientist and the role of an ML engineer.

Data Science 87

Data Science ML Engineer Data Scientist ML 87

Marktechpost

JANUARY 31, 2024

Data scientists and ML engineers often need help to build full-stack applications. These professionals typically have a firm grasp of data and AI algorithms. Still, they may need more skills or time to learn new languages or frameworks to create user-friendly web applications.

Data Scientist 135

Data Scientist Machine Learning Python ML Engineer 135

IBM Journey to AI blog

AUGUST 11, 2023

How to use ML to automate the refining process into a cyclical ML process. Initiate updates and optimization—Here, ML engineers will begin “retraining” the ML model method by updating how the decision process comes to the final decision, aiming to get closer to the ideal outcome.

Data Science 170

Data Science DevOps Machine Learning Data Scientist 170

Marktechpost

OCTOBER 10, 2024

Machine Learning Engineer : Specializes in building, optimizing, and deploying ML models. ML engineers often need to handle issues like model drift and data pipeline integration. Data scientists use ML algorithms to improve predictive models and deliver accurate insights.

Data Science 110

Data Science Machine Learning Data Scientist ML Engineer 110

IBM Journey to AI blog

AUGUST 12, 2024

MLOps platforms are primarily used by data scientists, ML engineers, DevOps teams and ITOps personnel who use them to automate and optimize ML models and get value from AI initiatives faster.

Big Data 266

Big Data DevOps Automation Machine Learning 266

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.

Machine Learning 113

Machine Learning ML Engineer DevOps ML 113

Flipboard

JUNE 20, 2023

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. This is important because training ML models and then using the trained models to make predictions (inference) can be highly energy-intensive tasks.

Machine Learning 123

Machine Learning BERT Deep Learning ML Engineer 123

TheSequence

NOVEMBER 7, 2024

But how good is AI in traditional machine learning(ML) engineering tasks such as training or validation. This is the purpose of a new work proposed by OpenAI with MLE-Bench, a benchmark to evaluate AI agents in ML engineering tasks. One of the ultimate manifestations of this proposition is AI writing AI code.

OpenAI 59

OpenAI ML Engineer Machine Learning AI 59

AWS Machine Learning Blog

SEPTEMBER 4, 2024

In this post, we introduce an example to help DevOps engineers manage the entire ML lifecycle—including training and inference—using the same toolkit. Solution overview We consider a use case in which an ML engineer configures a SageMaker model building pipeline using a Jupyter notebook.

DevOps 85

DevOps ML Engineer ML Metadata 85

Towards AI

JANUARY 30, 2024

ML Engineers(LLM), Tech Enthusiasts, VCs, etc. Anybody previously acquainted with ML terms should be able to follow along. How advanced is this post? Replicate my code here: [link] or through Colab PPO stands for proximal policy optimization in the context of solving RF problems.

Explainability 97

Explainability ML Engineer LLM ML 97

AWS Machine Learning Blog

JULY 8, 2024

TWCo data scientists and ML engineers took advantage of automation, detailed experiment tracking, integrated training, and deployment pipelines to help scale MLOps effectively. ML model experimentation is one of the sub-components of the MLOps architecture. We encourage to you to get started with Amazon SageMaker today.

Data Scientist 99

Data Scientist ML Engineer Machine Learning Data Science 99

Towards AI

NOVEMBER 8, 2024

Data preparation isn’t just a part of the ML engineering process — it’s the heart of it. Last Updated on November 9, 2024 by Editorial Team Author(s): Houssem Ben Braiek Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium.

Data Ingestion 99

Data Ingestion Metadata ML Engineer ML 99

Marktechpost

MAY 30, 2024

Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle.

Artificial Intelligence 132

Artificial Intelligence Artificial Intelligence BERT Computer Vision 132

AWS Machine Learning Blog

OCTOBER 20, 2023

An ML engineer deploys the model pipeline into the ML team test environment using a shared services CI/CD process. After stakeholder validation, the ML model is deployed to the team’s production environment. ML operations This module helps LOBs and ML engineers work on their dev instances of the model deployment template.

ML 110

ML Data Scientist ML Engineer Data Science 110

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. A Seamless Integration for Airbnb’s ML Practitioners Chronon has proven to be a game-changer for Airbnb’s ML practitioners.

Machine Learning 98

Machine Learning ML Engineer Data Ingestion ML 98

Marktechpost

NOVEMBER 16, 2024

It is ideal for ML engineers, data scientists, and technical leaders, providing real-world training for production-ready generative AI using Amazon Bedrock and cloud-native services.

Artificial Intelligence 105

Artificial Intelligence Artificial Intelligence Prompt Engineer Prompt Engineering 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. The solution illustrated in this post focuses on the new SageMaker Studio experience, particularly private JupyterLab and Code Editor spaces.

ML Engineer 94

ML Engineer Data Scientist Machine Learning ML 94

Salmon Run

DECEMBER 31, 2024

As an ML Engineer, we are generally tasked with solving some business problem with technology. Generally, unless it is a very simple problem, there would be more than one ML model involved, maybe different types of models depending on the sub-task, maybe other supporting tools such as a Search Index

ML 59

ML ML Engineer Software Engineer Python 59

Marktechpost

JANUARY 10, 2024

It also automates feature engineering, a task traditionally handled solely by ML engineers, saving time and reducing the risk of errors. The AutoML framework streamlines the content moderation classifier development process, significantly reducing the time required for model development and re-training.

Machine Learning 103

Machine Learning Continuous Learning ML Engineer Automation 103