O'Reilly Media

JANUARY 17, 2023

Figuring out what kinds of problems are amenable to automation through code. ” I, thankfully, learned this early in my career, at a time when I could still refer to myself as a software developer. Companies build or buy software to automate human labor, allowing them to eliminate existing jobs or help teams to accomplish more.

Automation 145

Automation Robotics Data Scientist ML 145

BAIR

MARCH 11, 2024

You can also turn on Disqus comments, but we recommend disabling this feature. --> Every year, the Berkeley Artificial Intelligence Research (BAIR) Lab graduates some of the most talented and innovative minds in artificial intelligence and machine learning. Currently, I am working on Large Language Model (LLM) based autonomous agents.

Robotics 337

Robotics Natural Language Processing Machine Learning Deep Learning 337

Towards AI

APRIL 4, 2023

SAN JOSE, CA (April 4, 2023) — Edge Impulse, the leading edge AI platform, today announced Bring Your Own Model (BYOM), allowing AI teams to leverage their own bespoke ML models and optimize them for any edge device. Praise Edge Impulse and its new features are garnering accolades from industry leaders.

ML Engineer 98

ML Engineer ML Python Neural Network 98

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 137

Machine Learning DevOps Data Scientist Data Quality 137

Unite.AI

JUNE 29, 2023

Business leaders in today's tech and startup scene know the importance of mastering AI and machine learning. They realize how it can help draw valuable insights from data, streamline operations through smart automation, and create unrivaled customer experiences.

Machine Learning 262

Machine Learning ML AI AI 262

Marktechpost

JANUARY 10, 2024

Automated Machine Learning (AutoML) has been introduced to address the pressing need for proactive and continual learning in content moderation defenses on the LinkedIn platform. It is a framework for automating the entire machine-learning process, specifically focusing on content moderation classifiers.

Machine Learning 102

Machine Learning Continuous Learning ML Engineer Automation 102

AWS Machine Learning Blog

FEBRUARY 29, 2024

Creating scalable and efficient machine learning (ML) pipelines is crucial for streamlining the development, deployment, and management of ML models. In this post, we present a framework for automating the creation of a directed acyclic graph (DAG) for Amazon SageMaker Pipelines based on simple configuration files.

Automation 122

Automation Python Machine Learning ML 122

ODSC - Open Data Science

SEPTEMBER 21, 2023

The majority of us who work in machine learning, analytics, and related disciplines do so for organizations with a variety of different structures and motives. The following is an extract from Andrew McMahon’s book , Machine Learning Engineering with Python, Second Edition.

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Machine Learning ML Engineer ML Data Science 98

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

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.

Data Science 170

Data Science DevOps Machine Learning Data Scientist 170

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. Take action today and unlock the full potential of your ML projects!

Machine Learning 129

Machine Learning ML Python Auto-complete 129

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. As businesses across industries increasingly embrace AI and ML to gain a competitive edge, the demand for MLOps Engineers has skyrocketed.

Software Engineer 182

Software Engineer DevOps Machine Learning ML 182

AWS Machine Learning Blog

OCTOBER 19, 2023

Customers increasingly want to use deep learning approaches such as large language models (LLMs) to automate the extraction of data and insights. For many industries, data that is useful for machine learning (ML) may contain personally identifiable information (PII).

Machine Learning 116

Machine Learning Python ML Automation 116

AWS Machine Learning Blog

FEBRUARY 11, 2025

Get started with SageMaker JumpStart SageMaker JumpStart is a machine learning (ML) hub that can help accelerate your ML journey. He focuses on helping customers build, deploy, and migrate ML production workloads to SageMaker at scale. Visit SageMaker JumpStart in SageMaker Studio now to get started.

ML 83

ML Machine Learning Python Computer Vision 83

AWS Machine Learning Blog

APRIL 7, 2025

This approach allows for greater flexibility and integration with existing AI and machine learning (AI/ML) workflows and pipelines. Enhanced Customer Experience through Automation and Personalization**: - **Automated Customer Support**: LLMs can power chatbots and virtual assistants that provide 24/7 customer support.

Machine Learning 89

Machine Learning Large Language Models Python Automation 89

AWS Machine Learning Blog

MARCH 18, 2025

Streamlined data collection and analysis Automating the process of extracting relevant data points from patient-physician interactions can significantly reduce the time and effort required for manual data entry and analysis, enabling more efficient clinical trial management.

LLM 112

LLM NLP Data Integration AI 112

ODSC - Open Data Science

JUNE 6, 2023

Be sure to check out their talk, “ Getting Up to Speed on Real-Time Machine Learning ,” there! The benefits of real-time machine learning are becoming increasingly apparent. This is due to a deep disconnect between data engineering and data science practices.

Machine Learning 90

Machine Learning ML Engineer Neural Network Data Science 90

AWS Machine Learning Blog

MARCH 22, 2023

Generating this data can take months to gather and require large teams of labelers to prepare it for use in machine learning (ML). Automating the whole workflow can help reduce manual work. In this post, we show how you can use AWS Step Functions to build and automate the workflow. Finally, install the AWS SAM CLI.

Automation 96

Automation Machine Learning ML Computer Vision 96

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 116

Data Science ML ML Engineer Data Scientist 116

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. Managers lacked the visibility needed for ongoing monitoring of ML workflows.

Data Scientist 120

Data Scientist ML Engineer Data Science Machine Learning 120

AWS Machine Learning Blog

FEBRUARY 12, 2025

Machine learning (ML) engineers must make trade-offs and prioritize the most important factors for their specific use case and business requirements. Along with protecting against toxicity and harmful content, it can also be used for Automated Reasoning checks , which helps you protect against hallucinations.

Auto-classification 89

Auto-classification Metadata Generative AI Machine Learning 89

AWS Machine Learning Blog

MARCH 1, 2023

Statistical methods and machine learning (ML) methods are actively developed and adopted to maximize the LTV. Continuous ML model retraining is one method to overcome this challenge by relearning from the most recent data. ML engineers no longer need to manage this training metadata separately.

Automation 101

Automation ETL Data Drift ML 101

AWS Machine Learning Blog

FEBRUARY 21, 2025

Data exploration and model development were conducted using well-known machine learning (ML) tools such as Jupyter or Apache Zeppelin notebooks. Deployment times stretched for months and required a team of three system engineers and four ML engineers to keep everything running smoothly.

Data Science 74

Data Science Data Scientist Data Ingestion DevOps 74

AWS Machine Learning Blog

OCTOBER 28, 2024

Real-world applications vary in inference requirements for their artificial intelligence and machine learning (AI/ML) solutions to optimize performance and reduce costs. Data Scientist at AWS, bringing a breadth of data science, ML engineering, MLOps, and AI/ML architecting to help businesses create scalable solutions on AWS.

ML 110

ML Metadata Data Scientist DevOps 110

Pickl AI

APRIL 19, 2023

Machine Learning is the part of Artificial Intelligence and computer science that emphasizes on the use of data and algorithms, imitating the way humans learn and improving accuracy. Machine Learning is becoming increasingly popular and crucial in today’s market for effective productivity and decision-making processes.

Machine Learning 52

Machine Learning ML Engineer Data Scientist ML 52

The MLOps Blog

MARCH 21, 2023

Moving across the typical machine learning lifecycle can be a nightmare. 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. How to understand your users (data scientists, ML engineers, etc.).

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

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 151

ML DevOps Data Scientist ML Engineer 151

ODSC - Open Data Science

APRIL 2, 2025

In 2025, artificial intelligence isnt just trendingits transforming how engineering teams build, ship, and scale software. Whether its automating code, enhancing decision-making, or building intelligent applications, AI is rewriting what it means to be a modern engineer. Jupyter notebooks remain a staple for data scientists.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models ML Engineer 52

Pickl AI

AUGUST 28, 2024

Summary: Vertex AI is a comprehensive platform that simplifies the entire Machine Learning lifecycle. Introduction In the rapidly evolving landscape of Machine Learning , Google Cloud’s Vertex AI stands out as a unified platform designed to streamline the entire Machine Learning (ML) workflow.

Machine Learning 52

Machine Learning ML Engineer ML Automation 52

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. Siamak Nariman is a Senior Product Manager at AWS. Madhubalasri B.

ML 99

ML Machine Learning Auto-complete Auto-classification 99

Pickl AI

NOVEMBER 28, 2024

Summary: The blog discusses essential skills for Machine Learning Engineer, emphasising the importance of programming, mathematics, and algorithm knowledge. Understanding Machine Learning algorithms and effective data handling are also critical for success in the field. billion by 2031, growing at a CAGR of 34.20%.

Machine Learning 52

Machine Learning Neural Network ML Engineer Algorithm 52

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

The MLOps Blog

JANUARY 26, 2024

Training and evaluating models is just the first step toward machine-learning success. For this, we have to build an entire machine-learning system around our models that manages their lifecycle, feeds properly prepared data into them, and sends their output to downstream systems. But what is an ML pipeline?

Machine Learning 72

Machine Learning Metadata ML Python 72

Towards AI

APRIL 27, 2023

for e.g., if a manufacturing or logistics company is collecting recording data from CCTV across its manufacturing hubs and warehouses, there could be a potentially a good number of use cases ranging from workforce safety, visual inspection automation, etc. 99% of consultants will rather ask you to actually execute these POCs.

Automation 98

Automation Auto-complete Computer Vision ChatGPT 98

AWS Machine Learning Blog

OCTOBER 22, 2024

It accelerates your generative AI journey from prototype to production because you don’t need to learn about specialized workflow frameworks to automate model development or notebook execution at scale. Specifically, you will learn how to: Access and navigate the new visual designer in Amazon SageMaker Studio.

Automation 87

Automation LLM DevOps Python 87

The MLOps Blog

JUNE 27, 2023

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors. This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

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