O'Reilly Media

MARCH 18, 2025

If you AIAWs want to make the most of AI, you’d do well to borrow some hard-learned lessons from the software development tech boom. And in return, software dev also needs to learn some lessons about AI. We’ve seen this movie before Earlier in my career I worked as a software developer.

Software Development 69

Software Development Python Data Scientist AI 69

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?

Data Science 170

Data Science DevOps Machine Learning Data Scientist 170

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.

ML 91

ML Machine Learning Auto-complete Auto-classification 91

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.

Software Engineer 176

Software Engineer DevOps Machine Learning ML 176

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. Admins can navigate to the IAM console, search for the SageMaker Studio role, and add the policy outlined in Set up Amazon Q Developer for your users.

ML 82

ML Computer Vision Data Scientist Machine Learning 82

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.

ML 88

ML Metadata Software Development Generative AI 88

O'Reilly Media

JANUARY 17, 2023

What would you say is the job of a software developer? A layperson, an entry-level developer, or even someone who hires developers will tell you that job is to … well … write software. They’d say that the job involves writing some software, sure. This mindset has followed me into my work in ML/AI.

Automation 145

Automation Robotics Data Scientist ML 145

O'Reilly Media

OCTOBER 19, 2021

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. What does a modern technology stack for streamlined ML processes look like? All ML projects are software projects.

DevOps 145

DevOps Software Engineer Data Scientist ML 145

Marktechpost

JUNE 19, 2024

It includes prompt engineering techniques, ethical considerations, and hands-on labs using tools like IBM Watsonx and GPT. Generative AI for Software Developers Specialization This IBM specialization teaches software developers to leverage generative AI for writing high-quality code, enhancing productivity and efficiency.

Artificial Intelligence 121

Artificial Intelligence Artificial Intelligence Prompt Engineering Prompt Engineer 121

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 112

Data Scientist ML Engineer Machine Learning Data Science 112

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

AWS Machine Learning Blog

NOVEMBER 21, 2023

By taking care of the undifferentiated heavy lifting, SageMaker allows you to focus on working on your machine learning (ML) models, and not worry about things such as infrastructure. Prior to working at Amazon Music, Siddharth was working at companies like Meta, Walmart Labs, Rakuten on E-Commerce centric ML Problems.

ML 103

ML Deep Learning Machine Learning DevOps 103

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

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. Prior to her current role, she spent several years at AWS focused on helping emerging GenAI startups develop models from ideation to production.

Data Scientist 72

Data Scientist Data Science ML Engineer Generative AI 72

ODSC - Open Data Science

APRIL 1, 2025

Building Multimodal AI Agents: Agentic RAG with Image, Text, and Audio Inputs Suman Debnath, Principal AI/ML Advocate at Amazon Web Services Discover the transformative potential of Multimodal Agentic RAG systems that integrate image, audio, and text to power intelligent, real-world applications.

Neural Network 52

Neural Network LLM Software Engineer AI 52

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. Experience working in data analysis, software development, and business is also crucial for an AI engineer.

AI Engineer 111

AI Engineer Software Engineer Artificial Intelligence Artificial Intelligence 111

Marktechpost

OCTOBER 23, 2023

With a meticulously crafted design offering extension points for seamless third-party integration, this innovation accelerates the execution of machine learning (ML) models on specialized hardware. Exemplar ML models running on the platform. The creators of ExecuTorch have thoughtfully provided the following: Extensive documentation.

ML 98

ML ML Engineer Software Development Machine Learning 98

AWS Machine Learning Blog

SEPTEMBER 25, 2024

SageMaker JumpStart is a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. SageMaker Studio is a comprehensive IDE that offers a unified, web-based interface for performing all aspects of the ML development lifecycle. Deploy Llama 3.2

Software Engineer 125

Software Engineer Software Development ML Python 125

AWS Machine Learning Blog

JANUARY 10, 2024

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development. The input to the training pipeline is the features dataset.

ML 121

ML Machine Learning Data Scientist ETL 121

AWS Machine Learning Blog

FEBRUARY 11, 2025

SageMaker Studio is a comprehensive IDE that offers a unified, web-based interface for performing all aspects of the machine learning (ML) development lifecycle. This approach allows for greater flexibility and integration with existing AI/ML workflows and pipelines. Deploy Meta SAM 2.1 Choose Delete again to confirm.

Computer Vision 81

Computer Vision ML Python Automation 81

Flipboard

SEPTEMBER 4, 2023

Envision yourself as an ML Engineer at one of the world’s largest companies. You make a Machine Learning (ML) pipeline that does everything, from gathering and preparing data to making predictions. What if we decouple the dependencies of the software we write from the hardware it works on? Enter the concept of Containers.

Machine Learning 153

Machine Learning Computer Vision Deep Learning Python 153

AWS Machine Learning Blog

JANUARY 17, 2023

Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) partly based on JupyterLab 3. Studio provides a web-based interface to interactively perform ML development tasks required to prepare data and build, train, and deploy ML models.

Software Engineer 91

Software Engineer ML ML Engineer Machine Learning 91

AWS Machine Learning Blog

APRIL 29, 2024

In 2024, however, organizations are using large language models (LLMs), which require relatively little focus on NLP, shifting research and development from modeling to the infrastructure needed to support LLM workflows. Metaflow’s coherent APIs simplify the process of building real-world ML/AI systems in teams.

ML 120

ML Python Data Scientist Machine Learning 120

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.

Neural Network 98

Neural Network Software Engineer Algorithm Machine Learning 98

TheSequence

OCTOBER 13, 2023

Join the global machine learning community at this virtual event to network and share best practices with your peers on platforms and architectures for production ML. Event Details - Date: Tuesday, November 14 - Time: 9:30AM – 3:00PM PT - Location: Virtual REGISTER NOW

ML Engineer 52

ML Engineer Software Engineer Data Scientist Software Development 52

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 119

Generative AI Metadata Python ML 119

Pickl AI

JANUARY 30, 2023

It’s a universal programming language that finds application in different technologies like AI, ML, Big Data and others. A Software Developer Uses Python: Backend Development : Python finds applications in developing server-side applications and APIs. The role of Python is not just limited to Data Science.

Python 97

Python DevOps Machine Learning Data Science 97

AWS Machine Learning Blog

MARCH 9, 2023

As machine learning (ML) models have improved, data scientists, ML engineers and researchers have shifted more of their attention to defining and bettering data quality. This has led to the emergence of a data-centric approach to ML and various techniques to improve model performance by focusing on data requirements.

ML Engineer 90

ML Engineer Data Scientist Convolutional Neural Networks ML 90

Towards AI

FEBRUARY 20, 2025

This week, we are introducing new frameworks through hands-on guides such as APDTFlow (addresses challenges with time series forecasting), NSGM (addresses variable selection and time-series network modeling), and MLFlow (streamlines ML workflows by tracking experiments, managing models, and more).

Neural Network 79

Neural Network Explainability LLM Software Development 79

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

AWS Machine Learning Blog

NOVEMBER 16, 2023

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.

Data Scientist 110

Data Scientist ML Data Science Machine Learning 110

AWS Machine Learning Blog

MAY 15, 2024

Next, we present the solution architecture and process flows for machine learning (ML) model building, deployment, and inferencing. Here, Amazon SageMaker Ground Truth allowed ML engineers to easily build the human-in-the-loop workflow (step v). We end with lessons learned. Burak is still a research affiliate in MIT.

Generative AI 124

Generative AI AI AI Machine Learning 124

AWS Machine Learning Blog

JULY 25, 2024

By accelerating the speed of issue detection and remediation, it increases the reliability of your ML training and reduces the wasted time and cost due to hardware failure. Ziwen Ning is a software development engineer at AWS. Geeta Gharpure is a senior software developer on the Annapurna ML engineering team.

Auto-complete 109

Auto-complete ML Software Development ML Engineer 109

Chatbots Life

MAY 16, 2023

10CLOUDS Year Founded : 2009 HQ : Warsaw, Poland Team Size : 51–200 employees Clients : TrustStamp (Identity verification), Emergent Tech (G-Coin), AlephZero (Blockchain), Tapeke (BitCoin Software Development), Tagasauris (Crowdsourcing Software Development), CallerSmart.

Generative AI 92

Generative AI Chatbots Conversational AI Software Development 92

Unite.AI

FEBRUARY 15, 2024

The people aspect underlines the need for skilled AI/ML engineers, data scientists, and software developers. Data readiness emphasizes the importance of high-quality training data, while concerns about data privacy and security are also raised.

Generative AI 100

Generative AI ML Engineer Data Scientist Software Development 100

AWS Machine Learning Blog

DECEMBER 13, 2023

Machine learning (ML) models do not operate in isolation. To deliver value, they must integrate into existing production systems and infrastructure, which necessitates considering the entire ML lifecycle during design and development. GitHub serves as a centralized location to store, version, and manage your ML code base.

ML 120

ML Automation Metadata Software Development 120

Heartbeat

FEBRUARY 1, 2023

Machine learning has become an essential part of our lives because we interact with various applications of ML models, whether consciously or unconsciously. Machine Learning Operations (MLOps) are the aspects of ML that deal with the creation and advancement of these models. What is MLOps?

DevOps 96

DevOps Machine Learning Data Scientist Software Engineer 96