AWS Machine Learning Blog

MARCH 10, 2025

The use of multiple external cloud providers complicated DevOps, support, and budgeting. Automated deployment strategy Our GitOps-embedded framework streamlines the deployment process by implementing a clear branching strategy for different environments. The system also enables rapid rollback capabilities if needed.

DevOps 90

DevOps Metadata Auto-complete Automation 90

IBM Journey to AI blog

SEPTEMBER 19, 2024

They created an Intelligent Feedback Analysis tool that automates the extraction and analysis of customer comments and reviews across the energy sector. They developed a ‘Clinical Coding Assistant’ solution that used natural language processing (NLP) and generative AI to extract and convert medical notes into standardized codes.

Generative AI 281

Generative AI DevOps Natural Language Processing NLP 281

AWS Machine Learning Blog

MAY 7, 2024

For all languages that are supported by Amazon Transcribe, you can find FMs from Hugging Face supporting summarization in corresponding languages The following diagram depicts the automated meeting summarization workflow. Mateusz Zaremba is a DevOps Architect at AWS Professional Services.

Automation 122

Automation Auto-complete DevOps UX Design 122

IBM Journey to AI blog

SEPTEMBER 20, 2023

They use self-supervised learning algorithms to perform a variety of natural language processing (NLP) tasks in ways that are similar to how humans use language (see Figure 1). IBM watsonx.governance is an end-to-end automated AI lifecycle governance toolkit that is built to enable responsible, transparent and explainable AI workflows.

Large Language Models 238

Large Language Models DevOps Data Science AI Modeling 238

Flipboard

FEBRUARY 10, 2025

Unlike traditional systems, which rely on rule-based automation and structured data, agentic systems, powered by large language models (LLMs), can operate autonomously, learn from their environment, and make nuanced, context-aware decisions. The following diagram illustrates the solution architecture. You can find Pranav on LinkedIn.

LLM 160

LLM AI AI Python 160

Becoming Human

APRIL 19, 2024

Automated Testing: By automating the creation of test cases, generative AI can expedite the software development process’ testing phase. This automated testing method improves software products’ overall reliability and quality. These include code creation, automated testing, and design support.

Software Development 103

Software Development Generative AI DevOps Automation 103

ODSC - Open Data Science

APRIL 12, 2023

Red Hat Since its start with the Red Hat® Enterprise Linux®, Red Hat has expanded its products to include agile integration, management and automation solutions, middleware, cloud-native application development, and hybrid cloud infrastructure. 25 years in, they remain committed to operating transparently, responsibly, and open source.

Data Science 97

Data Science Deep Learning DevOps Software Development 97

Explosion

JUNE 18, 2021

In this blog post, I’m going to discuss some of the biggest challenges for applied NLP and translating business problems into machine learning solutions. This blog post is based on talks I gave at the “Teaching NLP” workshop at NAACL 2021 and the L3-AI online conference. I call this “Applied NLP Thinking”. So where do you start?

NLP 52

NLP Machine Learning Natural Language Processing DevOps 52

AWS Machine Learning Blog

JANUARY 12, 2023

In this post, The Very Group shows how they use Amazon Comprehend to add a further layer of automated defense on top of policies to design threat modelling into all systems, to prevent PII from being sent in log data to Elasticsearch for indexing. Overview of solution.

DevOps 122

DevOps Natural Language Processing Metadata Automation 122

Mlearning.ai

JULY 31, 2023

Extension Of Devops MLOps is an extension of DevOps. DevOps aims to streamline the development and operation of software applications, while MLOps focuses on the machine learning lifecycle. MLOps extends DevOps by including data science practices, like model training and data preprocessing.

DevOps 52

DevOps Machine Learning Data Scientist NLP 52

AWS Machine Learning Blog

MARCH 1, 2023

Solution overview Amazon Comprehend is a fully managed service that uses natural language processing (NLP) to extract insights about the content of documents. MLOps focuses on the intersection of data science and data engineering in combination with existing DevOps practices to streamline model delivery across the ML development lifecycle.

Data Ingestion 93

Data Ingestion DevOps ML Automation 93

Marktechpost

DECEMBER 4, 2023

Trained on a large open-source code dataset, it suggests snippets to full functions, automating repetitive tasks and enhancing code quality. The ‘Notion AI is an AI system that may be used to automate a wide variety of writing tasks, from blogs and lists to brainstorming sessions and creative writing.

AI Tools 133

AI Tools Auto-complete Artificial Intelligence Artificial Intelligence 133

Marktechpost

JULY 4, 2023

Natural language processing (NLP) activities, including speech-to-text, sentiment analysis, text summarization, spell-checking, token categorization, etc., Regex generation Regular expression generation is time-consuming for developers; however, Autoregex.xyz leverages GPT-3 to automate the process.

Large Language Models 103

Large Language Models BERT Natural Language Processing Categorization 103

ODSC - Open Data Science

DECEMBER 1, 2023

Over the course of 3+ hours, you’ll learn How to take your machine learning model from experimentation to production How to automate your machine learning workflows by using GitHub Actions. You’ll explore the use of generative artificial intelligence (AI) models for natural language processing (NLP) in Azure Machine Learning.

Data Science 52

Data Science DevOps Machine Learning Large Language Models 52

Marktechpost

MAY 3, 2024

Trained on a large open-source code dataset, it suggests snippets to full functions, automating repetitive tasks and enhancing code quality. The ‘Notion AI is an AI system that may be used to automate a wide variety of writing tasks, from blogs and lists to brainstorming sessions and creative writing.

Artificial Intelligence 111

Artificial Intelligence Artificial Intelligence AI Tools Auto-complete 111

Marktechpost

JULY 5, 2024

These courses cover foundational topics such as machine learning algorithms, deep learning architectures, natural language processing (NLP), computer vision, reinforcement learning, and AI ethics. The curriculum also includes classical search, automated planning, and probabilistic graphical models for comprehensive AI training.

Data Science 60

Data Science Machine Learning Data Analysis Software Engineer 60

AWS Machine Learning Blog

SEPTEMBER 1, 2023

After the completion of the research phase, the data scientists need to collaborate with ML engineers to create automations for building (ML pipelines) and deploying models into production using CI/CD pipelines. All the produced models and code automation are stored in a centralized tooling account using the capability of a model registry.

Generative AI 120

Generative AI Prompt Engineer Prompt Engineering ML 120

Chatbots Life

MAY 16, 2023

Services : Mobile app development, web development, blockchain technology implementation, 360′ design services, DevOps, OpenAI integrations, machine learning, and MLOps. Services : AI Solution Development, ML Engineering, Data Science Consulting, NLP, AI Model Development, AI Strategic Consulting, Computer Vision.

Generative AI 92

Generative AI Chatbots Conversational AI Software Development 92

AWS Machine Learning Blog

AUGUST 16, 2023

Thomson Reuters Labs, the company’s dedicated innovation team, has been integral to its pioneering work in AI and natural language processing (NLP). This technology was one of the first of its kind, using NLP for more efficient and natural legal research. A key milestone was the launch of Westlaw Is Natural (WIN) in 1992.

Large Language Models 85

Large Language Models Machine Learning Generative AI ML 85

AWS Machine Learning Blog

NOVEMBER 7, 2023

Utilizing natural language processing (NLP), Amazon Kendra comprehends both the content of documents and the underlying intent of user queries, positioning it as a content retrieval tool for RAG based solutions. Reduced manual intervention – The automation reduces the need for human intervention, minimizing errors and ensuring consistency.

Large Language Models 111

Large Language Models Generative AI LLM AI 111

AWS Machine Learning Blog

OCTOBER 9, 2023

Sentiment analysis is a natural language processing (NLP) ready-to-use model that analyzes text for sentiments. He works with enterprise customers to build strategic, well-architected solutions and is passionate about automation. His expertise spans application architecture, DevOps, serverless, and machine learning.

Machine Learning 94

Machine Learning Categorization ML DevOps 94

Flipboard

MARCH 5, 2025

SimilarWeb data reveals dramatic AI market upheaval with Deepseek (8,658% growth) and Lovable (928% growth) dominating while traditional players like Microsoft and Tabnine lose significant market share. Read More

OpenAI 170

OpenAI AI AI DevOps 170

ODSC - Open Data Science

JULY 24, 2023

This firm is a leader in AI and NLP-powered no-code solutions that help build AI co-workers that help “automate complex people- and process-centric processes across functions.” This push for what they call “AI co-workers” allow companies to automate complex business processes that would normally keep their human employees focused.

Data Science 52

Data Science Chatbots Automation Big Data 52

AWS Machine Learning Blog

FEBRUARY 28, 2023

And we want to automate that anonymization to make this as scalable and amenable to self-service as possible. Automating also allows you to iterate the anonymization logic to meet your compliance requirements, and provides the ability to re-run the pipeline as your population’s health data changes. mg/actuat / salmeterol 0.05

ML 81

ML Machine Learning Categorization NLP 81

AWS Machine Learning Blog

NOVEMBER 14, 2023

Many of these foundation models have shown remarkable capability in understanding and generating human-like text, making them a valuable tool for a variety of applications, from content creation to customer support automation. However, these models are not without their challenges. In his free time, he enjoys playing chess and traveling.

ML 106

ML LLM Natural Language Processing Machine Learning 106

Heartbeat

OCTOBER 5, 2023

These LLMs can generate human-like text, understand context, and perform various Natural Language Processing (NLP) tasks. MLOps, often seen as a subset of DevOps (Development Operations), focuses on streamlining the development and deployment of machine learning models.

Large Language Models 52

Large Language Models DevOps Machine Learning Prompt Engineer 52

AWS Machine Learning Blog

AUGUST 29, 2023

In this post, we describe how to create an MLOps workflow for batch inference that automates job scheduling, model monitoring, retraining, and registration, as well as error handling and notification by using Amazon SageMaker , Amazon EventBridge , AWS Lambda , Amazon Simple Notification Service (Amazon SNS), HashiCorp Terraform, and GitLab CI/CD.

Data Scientist 82

Data Scientist Data Quality Python ML 82

ODSC - Open Data Science

JULY 19, 2023

The data science team is now expected to be equipped with CI/CD skills to sustain ongoing inference with retraining cycles and automated redeployments of models. The repository also features architecture specifically designed for Computer Vision (CV) and Natural Language Processing (NLP) use cases.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52

The MLOps Blog

APRIL 5, 2023

These teams may include but are not limited to data scientists, software developers, machine learning engineers, and DevOps engineers. Save and Load Machine Learning Models in Python with scikit-learn ML Explained – Aggregate Intellect – AI.SCIENCE Model Packaging Overview (NLP + MLOps workshop sneak peak)

ML 69

ML Machine Learning Deep Learning Metadata 69

Bugra Akyildiz

NOVEMBER 20, 2022

AI for DevOps to infuse AI/ML into the entire software development lifecycle to achieve high productivity. Use it to automate development workflows — including machine provisioning, model training and evaluation, comparing ML experiments across project history, and monitoring changing datasets.

ML 52

ML Data Science ETL DevOps 52

Explosion

AUGUST 3, 2017

We’ve been working on Prodigy since we first launched Explosion last year, alongside our open-source NLP library spaCy and our consulting projects (it’s been a busy year!). Most of those insights have been used to make spaCy better: AI DevOps was hard, so we made sure models could be installed via pip.

Python 52

Python Convolutional Neural Networks Machine Learning Algorithm 52

Heartbeat

FEBRUARY 29, 2024

Furthermore, the software development process has evolved to embrace Agile methodologies, DevOps practices, and continuous integration/continuous delivery (CI/CD) pipelines. These tools have evolved to support the demands of modern software engineering, offering features like real-time collaboration, code analysis, and automated testing.

Software Engineer 52

Software Engineer Software Development Large Language Models LLM 52

The MLOps Blog

OCTOBER 3, 2023

For me, it was a little bit of a longer journey because I kind of had data engineering and cloud engineering and DevOps engineering in between. That’s a huge part of what they do, so NLP is very big there, obviously. Mailchimp seeks to make it easier and to automate it. They’re terrible people. How awful are they?”

ML 52

ML Data Scientist Machine Learning Data Science 52

AWS Machine Learning Blog

JULY 16, 2024

This operator simplifies the process of running distributed training jobs by automating the deployment and scaling of the necessary components. See the following code: # Deploy Kubeflow training operator kubectl apply -k "github.com/kubeflow/training-operator/manifests/overlays/standalone?

Generative AI 120

Generative AI Auto-complete Auto-classification Deep Learning 120

IBM Journey to AI blog

JUNE 5, 2024

However, SaaS architectures can easily overwhelm DevOps teams with data aggregation, sorting and analysis tasks. Modern SaaS analytics solutions can seamlessly integrate with AI models to predict user behavior and automate data sorting and analysis; and ML algorithms enable SaaS apps to learn and improve over time.

DevOps 236

DevOps Automation ML Machine Learning 236

IBM Journey to AI blog

AUGUST 15, 2023

Recent AI developments are also helping businesses automate and optimize HR recruiting and professional development, DevOps and cloud management, and biotech research and manufacturing. Companies can create automated customer service workflows with customized AI models built on customer data.

Artificial Intelligence 234

Artificial Intelligence Artificial Intelligence Natural Language Processing AI 234

Unite.AI

OCTOBER 8, 2024

AI-augmented development redefines team collaboration by automating routine tasks such as bug detection, code reviews, and version control. This automation also promotes effective collaboration by minimizing bottlenecks and reducing the need for constant manual intervention.

Software Development 260

Software Development DevOps Automation AI 260