AWS Machine Learning Blog

MARCH 10, 2025

The use of multiple external cloud providers complicated DevOps, support, and budgeting. Operational consolidation and reliability Post-migration, our DevOps and SRE teams see 20% less maintenance burden and overheads. These operational inefficiencies meant that we had to revisit our solution architecture.

DevOps 99

DevOps Metadata Auto-complete Automation 99

IBM Journey to AI blog

FEBRUARY 14, 2024

Voice-based queries use natural language processing (NLP) and sentiment analysis for speech recognition so their conversations can begin immediately. With text to speech and NLP, AI can respond immediately to texted queries and instructions. Humanize HR AI can attract, develop and retain a skills-first workforce.

Computer Vision 247

Computer Vision NLP Robotics Automation 247

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). Large language models (LLMs) have taken the field of AI by storm.

Large Language Models 238

Large Language Models DevOps Data Science AI Modeling 238

ODSC - Open Data Science

MARCH 31, 2025

Solving this for traditional NLP problems or retrieval systems, or extracting knowledge from the documents to train models, continues to be challenging. That type of information expands the possibilities for traditional NLP use cases and use cases for retrieval systems like RAG and the creation of training datasets forLLMs.

Metadata 52

Metadata DevOps NLP Large Language Models 52

Unite.AI

JANUARY 25, 2024

Natural Language Processing (NLP), a field at the heart of understanding and processing human language, saw a significant increase in interest, with a 195% jump in engagement. This spike in NLP underscores its central role in the development and application of generative AI technologies.

Prompt Engineering 182

Prompt Engineering Prompt Engineer NLP Generative AI 182

Becoming Human

APRIL 19, 2024

Natural Language Processing (NLP) for Requirements: Generative AI is a useful technology for requirements analysis and collection since it can be used to interpret and comprehend natural language. This automated testing method improves software products’ overall reliability and quality.

Software Development 103

Software Development Generative AI DevOps Automation 103

Flipboard

FEBRUARY 10, 2025

He is currently focused on combining his background in software engineering, DevOps, and machine learning to help customers deliver machine learning workflows at scale. Bobby Lindsey is a Machine Learning Specialist at Amazon Web Services. Hes been in technology for over a decade, spanning various technologies and multiple roles.

LLM 161

LLM AI AI Python 161

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

MAY 7, 2024

Mateusz Zaremba is a DevOps Architect at AWS Professional Services. Mateusz supports customers at the intersection of machine learning and DevOps specialization, helping them to bring value efficiently and securely. She has been part of multiple NLP projects, from behavioral change in digital communication to fraud detection.

Automation 130

Automation Auto-complete DevOps UX Design 130

Unite.AI

JANUARY 15, 2024

Verdict CodePal stands out with its wide range of coding tools, NLP-driven code understanding, and multi-language support. Leverages Natural Language Processing (NLP) to understand code and provide explanations, enhancing code comprehension. DevOps The DevOps tools CodePal simplify code deployment and streamline coding tasks.

Explainability 147

Explainability DevOps AI AI 147

ODSC - Open Data Science

APRIL 12, 2023

Providing DevOps, product, and technical support, Comet enables organizations to personalize their experience on Comet’s platform, training their models with their own tools. It currently offers services in a wide range of industries, from life sciences to wholesale distribution.

Data Science 97

Data Science Deep Learning DevOps Software Development 97

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

JANUARY 12, 2023

Amazon Comprehend is a fully managed and continuously trained natural language processing (NLP) service that can extract insight about the content of a document or text. Overview of solution. The overriding goal for The Very Group’s engineering team was to prevent any PII data from reaching documents within Elasticsearch.

DevOps 128

DevOps Natural Language Processing Metadata Automation 128

Towards AI

FEBRUARY 15, 2024

Ramcharan12345 is looking to collaborate with AI devs who can leverage spaCy for NLP, utilize scikit-learn for supervised learning on historical data for symptom mapping, and implement TensorFlow/Keras for neural network-based risk prediction. Axer128 is looking for an HTML5/JavaScript/Python/C++ adept Programmer / DevOps.

AI 105

AI AI Neural Network DevOps 105

AWS Machine Learning Blog

SEPTEMBER 28, 2023

Each request/response interaction is facilitated by the AWS SDK and sends network traffic to Amazon Lex (the NLP component of the bot). Shuyu Yang is Generative AI and Large Language Model Delivery Lead and also leads CoE (Center of Excellence) Accenture AI (AWS DevOps professional) teams.

Generative AI 123

Generative AI Artificial Intelligence Artificial Intelligence Large Language Models 123

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 97

Data Ingestion DevOps ML Automation 97

Marktechpost

JULY 4, 2023

Natural language processing (NLP) activities, including speech-to-text, sentiment analysis, text summarization, spell-checking, token categorization, etc., A model’s parameters are the components learned from previous training data and, in essence, establish the model’s proficiency on a task, such as text generation.

Large Language Models 103

Large Language Models BERT Natural Language Processing Categorization 103

Marktechpost

DECEMBER 4, 2023

Includes many different types of artificial intelligence, such as image recognition, text analysis, and NLP. Its low latency and minimal overhead facilitate the research-to-production pipeline without requiring DevOps. You should write less code and construct more. Leap AI Developers can access Leap AI’s AI APIs.

AI Tools 133

AI Tools Auto-complete Artificial Intelligence Artificial Intelligence 133

ODSC - Open Data Science

DECEMBER 1, 2023

You’ll explore the use of generative artificial intelligence (AI) models for natural language processing (NLP) in Azure Machine Learning. First you’ll delve into the history of NLP, with a focus on how Transformer architecture contributed to the creation of large language models (LLMs).

Data Science 52

Data Science Machine Learning DevOps Large Language Models 52

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. Udacity offers comprehensive courses on AI designed to equip learners with essential skills in artificial intelligence.

Data Science 60

Data Science Machine Learning Data Analysis Software Engineer 60

Marktechpost

MAY 3, 2024

Includes many different types of artificial intelligence, such as image recognition, text analysis, and NLP. Its low latency and minimal overhead facilitate the research-to-production pipeline without requiring DevOps. You should write less code and construct more. Leap AI Developers can access Leap AI’s AI APIs.

Artificial Intelligence 111

Artificial Intelligence Artificial Intelligence AI Tools Auto-complete 111

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 92

Large Language Models Machine Learning Generative AI ML 92

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

OCTOBER 9, 2023

Sentiment analysis is a natural language processing (NLP) ready-to-use model that analyzes text for sentiments. His expertise spans application architecture, DevOps, serverless, and machine learning. Next, we explain how to review the trained model for performance. Sentiment analysis may be run for single line or batch predictions.

Machine Learning 103

Machine Learning Categorization ML DevOps 103

AWS Machine Learning Blog

SEPTEMBER 1, 2023

They have deep end-to-end ML and natural language processing (NLP) expertise and data science skills, and massive data labeler and editor teams. Therefore, DevOps and AppDevs (application developers on the cloud) personas need to follow best development practices to implement the functionality of input/output and rating.

Generative AI 126

Generative AI Prompt Engineering Prompt Engineer ML 126

AWS Machine Learning Blog

FEBRUARY 2, 2024

Embeddings capture the information content in bodies of text, allowing natural language processing (NLP) models to work with language in a numeric form. She is currently focusing on combining her DevOps and ML background into the domain of MLOps to help customers deliver and manage ML workloads at scale.

ETL 118

ETL DevOps LLM Generative AI 118

AWS Machine Learning Blog

SEPTEMBER 16, 2024

RAG is an approach that combines information retrieval techniques with natural language processing (NLP) to enhance the performance of text generation or language modeling tasks. With close to 6 years of experience at AWS, Shashi has developed deep expertise across a range of domains, including DevOps, analytics, and generative AI.

Deep Learning 117

Deep Learning Generative AI DevOps Machine Learning 117

AWS Machine Learning Blog

FEBRUARY 28, 2023

Use natural language processing (NLP) in Amazon HealthLake to extract non-sensitive data from unstructured blobs. We can see that Amazon HeathLake NLP interprets this as containing the condition “stroke” by querying for the condition record that has the same patient ID and displays “stroke.” mg/actuat / salmeterol 0.05

ML 90

ML Machine Learning Categorization NLP 90

AWS Machine Learning Blog

MAY 31, 2024

The output shows the expected JSON file content, illustrating the model’s natural language processing (NLP) and code generation capabilities. His area of focus is AI for DevOps and machine learning. An example usage is provided at the bottom, writing a dictionary with name, age, and city keys to a file named data.json.

Python 119

Python Machine Learning Auto-classification ML 119

AWS Machine Learning Blog

NOVEMBER 21, 2023

He specializes in Search, Retrieval, Ranking and NLP related modeling problems. Siddharth has a rich back-ground working on large scale machine learning problems that are latency sensitive e.g. Ads Targeting, Multi Modal Retrieval, Search Query Understanding etc.

ML 108

ML Deep Learning Machine Learning DevOps 108

AWS Machine Learning Blog

NOVEMBER 14, 2023

LLMs, like Llama2, have shown state-of-the-art performance on natural language processing (NLP) tasks when fine-tuned on domain-specific data. He previously worked in the semiconductor industry developing large computer vision (CV) and natural language processing (NLP) models to improve semiconductor processes.

ML 115

ML LLM Natural Language Processing Machine Learning 115

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

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. By using the high-accuracy search content from Kendra as a RAG payload, you can get better LLM responses.

Large Language Models 118

Large Language Models Generative AI LLM AI 118

AWS Machine Learning Blog

SEPTEMBER 23, 2024

She has a decade of experience in DevOps, infrastructure, and ML. He previously worked in the semiconductor industry developing large computer vision (CV) and natural language processing (NLP) models to improve semiconductor processes using state of the art ML techniques. Shibin Michaelraj is a Sr. You can find Pranav on LinkedIn.

ML 85

ML Computer Vision Data Scientist Machine Learning 85

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 Engineering 52

AWS Machine Learning Blog

APRIL 27, 2023

Solution overview With the onset of large language models, the field has seen tremendous progress on various natural language processing (NLP) benchmarks. Our proposed methods perform competitively to chain-of-thought prompting using the base Flan-T5, and ours is better at judging the correctness of its own answer.

Machine Learning 81

Machine Learning Large Language Models Categorization Natural Language Processing 81

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