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 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 131

Machine Learning DevOps Data Scientist Data Quality 131

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.

Machine Learning 98

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

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 112

Automation Python Machine Learning ML 112

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

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 120

Machine Learning ML Python Auto-complete 120

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 79

ML Machine Learning Python Computer Vision 79

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 106

Machine Learning Python ML Automation 106

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

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

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 91

Automation Machine Learning ML Computer Vision 91

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 98

Automation ETL Data Drift ML 98

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 110

Data Scientist ML Engineer Machine Learning Data Science 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

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 154

ML DevOps Data Scientist ML Engineer 154

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 81

Auto-classification Metadata Generative AI Machine Learning 81

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 68

Data Science Data Scientist Data Ingestion DevOps 68

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 Engineering 52

Prompt Engineering Prompt Engineer Large Language Models ML Engineer 52

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 99

ML Metadata Data Scientist DevOps 99

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

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

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 89

ML Machine Learning Auto-complete Auto-classification 89

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

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 79

LLM NLP Data Integration AI 79

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

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 81

Automation LLM DevOps Python 81

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. Many machine learning projects fail to deliver practical results due to difficulties in automation and deployment.

Machine Learning 52

Machine Learning ML Automation Data Scientist 52

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.

Data Science 129

Data Science Data Drift DevOps Auto-complete 129

Pickl AI

JANUARY 30, 2023

Versatile programming language- You can use Python for web development, Data Science, Machine Learning, Artificial Intelligence, finance and in many other domains. Data Automation: Automate data processing pipelines and workflows using Python scripting and libraries such as PyAutoGUI and Task Scheduler.

Python 97

Python DevOps Machine Learning Data Science 97

AWS Machine Learning Blog

JUNE 27, 2023

When machine learning (ML) models are deployed into production and employed to drive business decisions, the challenge often lies in the operation and management of multiple models. That is where Provectus , an AWS Premier Consulting Partner with competencies in Machine Learning, Data & Analytics, and DevOps, stepped in.

DevOps 112

DevOps ML Machine Learning ML Engineer 112

Unite.AI

FEBRUARY 28, 2024

Adversarial attacks Adversarial attacks involve specially crafted inputs designed to deceive machine learning models and trigger unintended behaviors. Data poisoning This attack involves injecting tainted data into the training pipeline of machine learning models to deliberately corrupt them.

Large Language Models 162

Large Language Models Machine Learning LLM Neural Network 162