IBM Journey to AI blog

AUGUST 11, 2023

The process for monitoring and addressing issues in the models once in production. How to use ML to automate the refining process into a cyclical ML process. Repeat—Teams will go through each step of the ML pipeline again until they’ve achieved the desired outcome.

Data Science 170

Data Science DevOps Machine Learning Data Scientist 170

ODSC - Open Data Science

APRIL 9, 2025

With advances in natural language processing and vision models, AI is now helping to populate and refine graph structures, especially in unstructured domains like legal documentation or scientific literature. In use cases like autonomous agents, graph-based orchestration offers structure and memory that pure neural networkslack.

Explainability 52

Explainability Natural Language Processing AI AI 52

AWS Machine Learning Blog

FEBRUARY 12, 2025

Large language models (LLMs) have revolutionized the field of natural language processing with their ability to understand and generate humanlike text. About the authors Daniel Zagyva is a Senior ML Engineer at AWS Professional Services.

LLM 80

LLM ML Natural Language Processing Machine Learning 80

AWS Machine Learning Blog

MARCH 18, 2025

Intelligent insights and recommendations Using its large knowledge base and advanced natural language processing (NLP) capabilities, the LLM provides intelligent insights and recommendations based on the analyzed patient-physician interaction. These insights can include: Potential adverse event detection and reporting.

LLM 113

LLM NLP Data Integration AI 113

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 123

Machine Learning BERT Deep Learning ML Engineer 123

AWS Machine Learning Blog

MARCH 22, 2024

Before joining AWS, he worked for AWS customers and partners in software engineering, consulting, and architecture roles for 8+ years. Aris Tsakpinis is a Specialist Solutions Architect for AI & Machine Learning with a special focus on natural language processing (NLP), large language models (LLMs), and generative AI.

Large Language Models 118

Large Language Models Natural Language Processing NLP Software Engineer 118

Marktechpost

JULY 25, 2024

It is ideal for ML engineers, data scientists, and technical leaders, providing real-world training for production-ready generative AI using Amazon Bedrock and cloud-native services. Students learn about key innovations, ethical challenges, and hands-on labs for generating text with Python.

Large Language Models 113

Large Language Models Prompt Engineering Prompt Engineer Chatbots 113

Unite.AI

JUNE 19, 2024

Master's Degree : Pursuing a Master's degree in Computer Science, Data Science, or a related field can further enhance your knowledge and skills, particularly in areas like ML, AI, and advanced software engineering concepts.

Software Engineer 182

Software Engineer DevOps Machine Learning ML 182

AWS Machine Learning Blog

FEBRUARY 26, 2024

Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP), improving tasks such as language translation, text summarization, and sentiment analysis. Rushabh Lokhande is a Senior Data & ML Engineer with AWS Professional Services Analytics Practice.

Large Language Models 137

Large Language Models LLM Big Data Machine Learning 137

AWS Machine Learning Blog

MARCH 13, 2024

The traditional method of training an in-house classification model involves cumbersome processes such as data annotation, training, testing, and model deployment, requiring the expertise of data scientists and ML engineers. LLMs, in contrast, offer a high degree of flexibility.

Natural Language Processing 134

Natural Language Processing LLM Prompt Engineer Prompt Engineering 134

Towards AI

JANUARY 6, 2025

Artificial Intelligence graduate certificate by STANFORD SCHOOL OF ENGINEERING Artificial Intelligence graduate certificate; taught by Andrew Ng, and other eminent AI prodigies; is a popular course that dives deep into the principles and methodologies of AI and related fields.

Artificial Intelligence 105

Artificial Intelligence Artificial Intelligence Computer Vision Deep Learning 105

BAIR

MARCH 11, 2024

Their work at BAIR, ranging from deep learning, robotics, and natural language processing to computer vision, security, and much more, has contributed significantly to their fields and has had transformative impacts on society. Currently, I am working on Large Language Model (LLM) based autonomous agents.

Robotics 100

Robotics Machine Learning Natural Language Processing Deep Learning 100

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. She leads machine learning projects in various domains such as computer vision, natural language processing, and generative AI.

Auto-classification 89

Auto-classification Metadata Generative AI Machine Learning 89

AWS Machine Learning Blog

DECEMBER 14, 2023

Our pipeline belongs to the general ETL (extract, transform, and load) process family that combines data from multiple sources into a large, central repository. At the same time, the same solution can be deployed to production by an ML Engineer with little modifications needed.

ETL 111

ETL Data Scientist Machine Learning Deep Learning 111

Towards AI

AUGUST 25, 2023

Any competent software engineer can implement any algorithm. Even if you are an experienced AI/ML engineer, you should know the performance of simpler models on your dataset/problem. Natural Language Processing with Python — Analyzing Text with the Natural Language Toolkit. Klein, and E.

Machine Learning 98

Machine Learning Software Engineer Neural Network Data Science 98

AWS Machine Learning Blog

MARCH 14, 2024

Amazon Kendra uses natural language processing (NLP) to understand user queries and find the most relevant documents. Grace Lang is an Associate Data & ML engineer with AWS Professional Services. Mike Amjadi is a Data & ML Engineer with AWS ProServe focused on enabling customers to maximize value from data.

Generative AI 130

Generative AI LLM AI AI 130

Chatbots Life

MAY 16, 2023

Services : AI Solution Development, ML Engineering, Data Science Consulting, NLP, AI Model Development, AI Strategic Consulting, Computer Vision. Data Monsters can help companies deploy, train and test machine learning pipelines for natural language processing and computer vision.

Generative AI 92

Generative AI Chatbots Conversational AI Software Development 92

AWS Machine Learning Blog

FEBRUARY 28, 2024

Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. This generative AI task is called text-to-SQL, which generates SQL queries from natural language processing (NLP) and converts text into semantically correct SQL.

Metadata 135

Metadata Generative AI LLM NLP 135

AWS Machine Learning Blog

APRIL 29, 2024

Historically, natural language processing (NLP) would be a primary research and development expense. In 2024, however, organizations are using large language models (LLMs), which require relatively little focus on NLP, shifting research and development from modeling to the infrastructure needed to support LLM workflows.

ML 127

ML Python Data Scientist Machine Learning 127

AWS Machine Learning Blog

FEBRUARY 21, 2025

The concept of a compound AI system enables data scientists and ML engineers to design sophisticated generative AI systems consisting of multiple models and components. His area of research is all things natural language (like NLP, NLU, and NLG). The following diagram compares predictive AI to generative AI.

LLM 87

LLM AI AI Data Scientist 87

AWS Machine Learning Blog

JULY 24, 2024

Large language models (LLMs) have achieved remarkable success in various natural language processing (NLP) tasks, but they may not always generalize well to specific domains or tasks. You can customize the model using prompt engineering, Retrieval Augmented Generation (RAG), or fine-tuning.

LLM 131

LLM ML Generative AI Machine Learning 131

AWS Machine Learning Blog

JANUARY 25, 2023

Amazon SageMaker Clarify is a feature of Amazon SageMaker that enables data scientists and ML engineers to explain the predictions of their ML models. It uses model agnostic methods like SHapely Additive exPlanations (SHAP) for feature attribution.

Explainability 89

Explainability Algorithm Natural Language Processing Machine Learning 89

AWS Machine Learning Blog

OCTOBER 23, 2023

Given this mission, Talent.com and AWS joined forces to create a job recommendation engine using state-of-the-art natural language processing (NLP) and deep learning model training techniques with Amazon SageMaker to provide an unrivaled experience for job seekers. The recommendation system has driven an 8.6%

NLP 119

NLP Deep Learning Machine Learning Natural Language Processing 119

AWS Machine Learning Blog

MAY 13, 2024

Evaluating LLMs is an undervalued part of the machine learning (ML) pipeline. We benchmark the results with a metric used for evaluating summarization tasks in the field of natural language processing (NLP) called Recall-Oriented Understudy for Gisting Evaluation (ROUGE).

Generative AI 133

Generative AI Prompt Engineering Prompt Engineer LLM 133

Pickl AI

NOVEMBER 28, 2024

Fundamental Programming Skills Strong programming skills are essential for success in ML. This section will highlight the critical programming languages and concepts ML engineers should master, including Python, R , and C++, and an understanding of data structures and algorithms. during the forecast period.

Machine Learning 52

Machine Learning Neural Network ML Engineer Algorithm 52

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. Security SMEs review the architecture based on business security policies and needs.

Generative AI 129

Generative AI Prompt Engineer Prompt Engineering ML 129

AWS Machine Learning Blog

FEBRUARY 12, 2024

The Ranking team at Booking.com learned that migrating to the cloud and SageMaker has proved beneficial, and that adapting machine learning operations (MLOps) practices allows their ML engineers and scientists to focus on their craft and increase development velocity. Daniel Zagyva is a Data Scientist at AWS Professional Services.

ML 135

ML Explainability Machine Learning Deep Learning 135

Heartbeat

OCTOBER 23, 2023

The Role of Data Scientists and ML Engineers in Health Informatics At the heart of the Age of Health Informatics are data scientists and ML engineers who play a critical role in harnessing the power of data and developing intelligent algorithms.

Data Scientist 52

Data Scientist Machine Learning Big Data Algorithm 52

AWS Machine Learning Blog

JUNE 23, 2023

It stands out when it comes to developing serverless applications with RESTful microservices and use cases requiring ML inference at scale across multiple industries. Its ease and built-in functionalities like the automatic API documentation make it a popular choice amongst ML engineers to deploy high-performance inference APIs.

Large Language Models 101

Large Language Models ML Python Machine Learning 101

Pickl AI

JANUARY 29, 2024

ML focuses on enabling computers to learn from data and improve performance over time without explicit programming. AI comprises Natural Language Processing, computer vision, and robotics. ML focuses on algorithms like decision trees, neural networks, and support vector machines for pattern recognition.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

AWS Machine Learning Blog

AUGUST 16, 2023

Thomson Reuters (TR), a global content and technology-driven company, has been using artificial intelligence (AI) and machine learning (ML) in its professional information products for decades. Thomson Reuters Labs, the company’s dedicated innovation team, has been integral to its pioneering work in AI and natural language processing (NLP).

Large Language Models 93

Large Language Models Machine Learning Generative AI ML 93

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Throughout this exercise, you use Amazon Q Developer in SageMaker Studio for various stages of the development lifecycle and experience firsthand how this natural language assistant can help even the most experienced data scientists or ML engineers streamline the development process and accelerate time-to-value.

ML 88

ML Computer Vision Data Scientist Machine Learning 88

AWS Machine Learning Blog

JANUARY 13, 2023

At the application level, such as computer vision, natural language processing, and data mining, data scientists and engineers only need to write the model, data, and trainer in the same way as a standalone program and then pass it to the FedMLRunner object to complete all the processes, as shown in the following code.

Machine Learning 96

Machine Learning ML Algorithm Data Scientist 96

Chatbots Life

MAY 12, 2023

We will discuss how models such as ChatGPT will affect the work of software engineers and ML engineers. Will ChatGPT replace software engineers? Will ChatGPT replace ML Engineers? this means that language models are just a higher level of abstraction for the developers. Why is ChatGPT so effective?

ChatGPT 90

ChatGPT Software Engineer NLP ML Engineer 90

AWS Machine Learning Blog

OCTOBER 19, 2023

Amazon Comprehend is a natural language processing (NLP) service that uses ML to uncover insights and relationships in unstructured data, with no managing infrastructure or ML experience required. It provides functionality to locate various PII entity types within text, for example names or credit card numbers.

Machine Learning 117

Machine Learning Python ML Automation 117

Snorkel AI

MAY 4, 2023

Large Language Models (LLMs) such as GPT-4 and LLaMA have revolutionized natural language processing and understanding, enabling a wide range of applications, from conversational AI to advanced text generation. 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.

Computer Vision 52

Computer Vision Large Language Models Natural Language Processing AI 52

Snorkel AI

MAY 4, 2023

Large Language Models (LLMs) such as GPT-4 and LLaMA have revolutionized natural language processing and understanding, enabling a wide range of applications, from conversational AI to advanced text generation. 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.

Computer Vision 52

Computer Vision Large Language Models Natural Language Processing AI 52