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

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.

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Generative AI Chatbots Conversational AI Software Development 98

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 94

Machine Learning BERT Deep Learning ML Engineer 94

Pickl AI

JANUARY 30, 2023

A Software Developer Uses Python: Backend Development : Python finds applications in developing server-side applications and APIs. The developer will use frameworks such as Django and Flask for this. Model Development: Use libraries such as TensorFlow, Keras, PyTorch, scikit-learn, etc.,

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Python DevOps Machine Learning Automation 97

Towards AI

AUGUST 24, 2023

Since this is an AI website, I will assume that most readers will have the following goals: You are interested in becoming an AI/ML engineer. You are interested in learning software engineering best practices [1][2]. In fact, more algorithms are constantly being developed.

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Software Engineer Neural Network Algorithm AI Engineer 98

AWS Machine Learning Blog

JANUARY 17, 2023

In Studio, you can load data, adjust ML models, move in between steps to adjust experiments, compare results, and deploy ML models for inference. The AWS Cloud Development Kit (AWS CDK) is an open-source software development framework to create AWS CloudFormation stacks through automatic CloudFormation template generation.

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Software Engineer ML Engineer ML Machine Learning 79

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. This post is co-written with Jayadeep Pabbisetty, Sr.

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ML Machine Learning ETL Data Scientist 106

Snorkel AI

MAY 4, 2023

Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. The free virtual conference is the largest annual gathering of the data-centric AI community.

Computer Vision 52

Computer Vision Large Language Models AI AI 52

Snorkel AI

MAY 4, 2023

Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. The free virtual conference is the largest annual gathering of the data-centric AI community.

Computer Vision 52

Computer Vision Large Language Models AI AI 52

ODSC - Open Data Science

JANUARY 10, 2024

The AI Paradigm Shift: Under the Hood of a Large Language Models Valentina Alto | Azure Specialist — Data and Artificial Intelligence | Microsoft Develop an understanding of Generative AI and Large Language Models, including the architecture behind them, their functioning, and how to leverage their unique conversational capabilities.

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Large Language Models LLM Deep Learning ML 52

AWS Machine Learning Blog

JANUARY 26, 2024

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. Lastly, we connect these together with an example LLM workload to describe an approach towards architecting with defense-in-depth security across trust boundaries.

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Generative AI LLM ML AI 129

Heartbeat

FEBRUARY 1, 2023

Machine Learning Operations (MLOps) are the aspects of ML that deal with the creation and advancement of these models. In this article, we’ll learn everything there is to know about these operations and how ML engineers go about performing them. What is MLOps?

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DevOps Machine Learning Data Scientist Software Engineer 96

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.

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Data Scientist ML Data Science Automation 95

AWS Machine Learning Blog

DECEMBER 13, 2023

ML operations, known as MLOps, focus on streamlining, automating, and monitoring ML models throughout their lifecycle. Data scientists, ML engineers, IT staff, and DevOps teams must work together to operationalize models from research to deployment and maintenance.

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ML Automation Metadata Software Development 107

AWS Machine Learning Blog

NOVEMBER 21, 2023

Prior to working at Amazon Music, Siddharth was working at companies like Meta, Walmart Labs, Rakuten on E-Commerce centric ML Problems. Tarun Sharma is a Software Development Manager leading Amazon Music Search Relevance. Siddharth spent early part of his career working with bay area ad-tech startups.

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AWS Machine Learning Blog

JUNE 8, 2023

Victor Rojo is a highly experienced technologist who is passionate about the latest in AI, ML, and software development. Ryan Gomes is a Data & ML Engineer with the AWS Professional Services Intelligence Practice. He leads the NYC machine learning and AI meetup.

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Generative AI LLM Large Language Models Machine Learning 76

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.

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ML DevOps Data Scientist ML Engineer 95

The MLOps Blog

SEPTEMBER 7, 2023

Have you ever talked to your Front-end or Back-end engineer peers and noticed how much they care about code quality? Writing legible, reusable, and efficient code has always been a challenge in the software development community. This situation is not different in the ML world. Aside neptune.ai What’s next?

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Software Engineer Machine Learning ETL ML Engineer 52

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.

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Automation Robotics Data Scientist Software Development 130

Marktechpost

OCTOBER 23, 2023

ExecuTorch ships with a Software Developer Kit (SDK) and toolchain, delivering an intuitive user experience for ML Developers. This seamless workflow empowers developers to transition from model authoring to training seamlessly and, finally, to device delegation within a single PyTorch environment.

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ML ML Engineer Software Development Machine Learning 98

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.

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ML Python Data Scientist Deep Learning 103

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.

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ML Engineer Data Scientist Convolutional Neural Networks ML 81

The MLOps Blog

JANUARY 23, 2023

Just so you know where I am coming from: I have a heavy software development background (15+ years in software). Came to ML from software. Founded two successful software services companies. Founded neptune.ai , a modular MLOps component for ML metadata store , aka “experiment tracker + model registry”.

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DevOps Metadata Software Engineer Data Scientist 59

AWS Machine Learning Blog

MAY 5, 2023

Solution overview Ground Truth is a fully self-served and managed data labeling service that empowers data scientists, machine learning (ML) engineers, and researchers to build high-quality datasets. Zhuling Bai is a Software Development Engineer at Amazon Web Services.

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Metadata Computer Vision Machine Learning Data Scientist 80

The MLOps Blog

MARCH 15, 2023

Collaborative development and version control Version control is quite crucial in modern software development that helps teams keep track of changes to their code over time. Git is a distributed version control system for software development.

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ETL Data Drift Machine Learning ML 52

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 109

Machine Learning Computer Vision Deep Learning Python 109

Viso.ai

MARCH 29, 2024

MLflow is an open-source platform designed to manage the entire machine learning lifecycle, making it easier for ML Engineers, Data Scientists, Software Developers, and everyone involved in the process. Experiment Tracking: Numerous configuration options (data, hyperparameters, pre-processing) impact ML outcomes.

Machine Learning 52

Machine Learning ML Automation Data Scientist 52

O'Reilly Media

OCTOBER 19, 2021

While there isn’t an authoritative definition for the term, it shares its ethos with its predecessor, the DevOps movement in software engineering: by adopting well-defined processes, modern tooling, and automated workflows, we can streamline the process of moving from development to robust production deployments. Versioning.

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DevOps Software Engineer Data Scientist ML 138

AWS Machine Learning Blog

OCTOBER 2, 2023

Use case: Inspecting the quality of metal tags As an ML engineer, it’s important to understand the business case you are working on. With a passion for automation, Joerg has worked as a software developer, DevOps engineer, and Site Reliability Engineer in his pre-AWS life.

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DevOps Automation ML Computer Vision 97

Mlearning.ai

AUGUST 18, 2023

As a software developer the more versed you are in DevOps the better you can foresee issues, fix bugs and be a valued team member. As an ML engineer you’re in charge of some code/model. Same analogy applies to MLOps.

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DevOps Python ML ML Engineer 52

AWS Machine Learning Blog

SEPTEMBER 29, 2023

Planet and AWS’s partnership on geospatial ML SageMaker geospatial capabilities empower data scientists and ML engineers to build, train, and deploy models using geospatial data. This is a powerful tool for data scientists and developers who want to work with satellite imagery and other geospatial data.

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Machine Learning ML Data Scientist Python 119

AWS Machine Learning Blog

APRIL 25, 2023

This allows ML engineers and admins to configure these environment variables so data scientists can focus on ML model building and iterate faster. About the Authors Dipankar Patro is a Software Development Engineer at AWS SageMaker, innovating and building MLOps solutions to help customers adopt AI/ML solutions at scale.

Machine Learning 82

Machine Learning Data Scientist Python ML 82

Flipboard

MARCH 7, 2023

There are also limited options for ad hoc script customization by users, such as data scientists or ML engineers, due to permissions of the user profile execution role. He develops and codes cloud native solutions with a focus on big data, analytics, and data engineering.

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Python Automation Data Scientist ML 93

The MLOps Blog

AUGUST 4, 2023

Strap in as we embark on this journey to streamline your ML project management. Machine learning monorepo | Source: Author A monorepo (short for monolithic repository) is a software development strategy where code for many projects is stored in the same repository. What is a monorepo? Here are a few notable examples.

ML 52

ML Machine Learning Python Software Engineer 52

AWS Machine Learning Blog

APRIL 19, 2024

of the SageMaker ACK Operators adds support for inference components , which until now were only available through the SageMaker API and the AWS Software Development Kits (SDKs). About the Authors Rajesh Ramchander is a Principal ML Engineer in Professional Services at AWS. Release v1.2.9

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Metadata LLM Software Development Machine Learning 104

The MLOps Blog

JULY 18, 2023

And even on the operation side of things, is there a separate operations team, and then you have your research or ml engineers doing these pipelines and stuff? In terms of the team set-up, does the team sort of leverage language experts in some sense, or how do you leverage language experts? Basically, how’s your team set up?

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Conversational AI Natural Language Processing AI AI 52

The MLOps Blog

MARCH 21, 2023

As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale. In this comprehensive guide, we’ll explore everything you need to know about machine learning platforms, including: Components that make up an ML platform.

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Machine Learning Data Scientist ML Metadata 69