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. For more information on application security, refer to Safeguard a generative AI travel agent with prompt engineering and Amazon Bedrock Guardrails. Nitin Eusebius is a Sr.

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Auto-classification Metadata Generative AI Machine Learning 95

Towards AI

MAY 30, 2024

The broad range of topics covered with easy to understand examples will help any readers, and developers be in the know of the theory behind LLMs, prompt engineering, RAG, orchestration platforms and more. The defacto manual for AI Engineering. I highly recommend this book.” Seriously, pick it up.” Ahmed Moubtahij, ing.,

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Prompt Engineer Prompt Engineering LLM NLP 108

AWS Machine Learning Blog

MARCH 13, 2024

The audio moderation workflow uses Amazon Transcribe Toxicity Detection, which is a machine learning (ML)-powered capability that uses audio and text-based cues to identify and classify voice-based toxic content across seven categories, including sexual harassment, hate speech, threats, abuse, profanity, insults, and graphic language.

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Natural Language Processing LLM Prompt Engineer Prompt Engineering 136

AWS Machine Learning Blog

MAY 30, 2024

Prompt engineering Prompt engineering is crucial for the knowledge retrieval system. The prompt guides the LLM on how to respond and interact based on the user question. Prompts also help ground the model. These factors led to the selection of Amazon Aurora PostgreSQL as the store for vector embeddings.

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Chatbots Prompt Engineer Prompt Engineering Large Language Models 130

Towards AI

JANUARY 6, 2025

You may get hands-on experience in Generative AI, automation strategies, digital transformation, prompt engineering, etc. AI engineering professional certificate by IBM AI engineering professional certificate from IBM targets fundamentals of machine learning, deep learning, programming, computer vision, NLP, etc.

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Artificial Intelligence Artificial Intelligence Computer Vision Deep Learning 105

Towards AI

SEPTEMBER 22, 2023

There were significant distinctions between academic researchers, ML practitioners, and their clients. ML consultants, who make a living by providing ML services may ask: How do we justify our profession in this scenario if the researchers are solving practical issues and the clients can use the cutting-edge AI tools on their own?

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Prompt Engineering Prompt Engineer ML ML Engineer 59

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. With a background in AI/ML, data science, and analytics, Yunfei helps customers adopt AWS services to deliver business results.

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LLM AI AI Data Scientist 94

TheSequence

JANUARY 19, 2024

You probably don’t need ML engineers In the last two years, the technical sophistication needed to build with AI has dropped dramatically. ML engineers used to be crucial to AI projects because you needed to train custom models from scratch. At the same time, the capabilities of AI models have grown.

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Prompt Engineering Prompt Engineer Generative AI Large Language Models 59

AWS Machine Learning Blog

JULY 24, 2024

You can customize the model using prompt engineering, Retrieval Augmented Generation (RAG), or fine-tuning. Fine-tuning an LLM can be a complex workflow for data scientists and machine learning (ML) engineers to operationalize. Each iteration can be considered a run within an experiment.

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LLM ML Generative AI Machine Learning 129

Towards AI

FEBRUARY 20, 2025

This week, we are introducing new frameworks through hands-on guides such as APDTFlow (addresses challenges with time series forecasting), NSGM (addresses variable selection and time-series network modeling), and MLFlow (streamlines ML workflows by tracking experiments, managing models, and more).

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Neural Network Explainability LLM Software Development 79

Towards AI

JUNE 18, 2024

The principles of CNNs and early vision transformers are still important as a good background for ML engineers, even though they are much less popular nowadays. The book focuses on adapting large language models (LLMs) to specific use cases by leveraging Prompt Engineering, Fine-Tuning, and Retrieval Augmented Generation (RAG).

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Large Language Models Prompt Engineer Prompt Engineering LLM 79

AWS Machine Learning Blog

OCTOBER 4, 2023

Solution overview Amazon SageMaker is built on Amazon’s two decades of experience developing real-world ML applications, including product recommendations, personalization, intelligent shopping, robotics, and voice-assisted devices. John helps customers design and optimize AI/ML workloads on AWS to help them achieve their business goals.

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LLM Large Language Models ML Data Scientist 119

The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

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Machine Learning Metadata Data Scientist Data Quality 134

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? Will ChatGPT replace ML Engineers? We will answer the question “ Will you lose your job?” And, as mentioned before.

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ChatGPT Software Engineer NLP ML Engineer 90

AWS Machine Learning Blog

APRIL 25, 2023

Data scientists typically carry out several iterations of experimentation in data processing and training models while working on any ML problem. They want to run this ML code and carry out the experimentation with ease of use and minimal code change.

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Machine Learning Data Scientist Python ML 101

The MLOps Blog

AUGUST 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. Stefan: Yeah.

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ML Data Scientist Software Engineer Machine Learning 52

TheSequence

NOVEMBER 12, 2023

📌 ML Engineering Event: Join Meta, PepsiCo, RiotGames, Uber & more at apply(ops) apply(ops) is in two days! Databricks’ CEO Ali Ghodsi will also be joining Tecton CEO Mike Del Balso for a fireside chat about LLMs, real-time ML, and other trends in ML. Register today—it’s free!

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OpenAI Generative AI ML Prompt Engineer 64

ODSC - Open Data Science

NOVEMBER 25, 2024

Some of our most popular in-person sessions at ODSC East were: Tackling Socioeconomic Bias in Machine Learning Managing the Volatility of AI Applications Building High-Quality Domain-Specific Models with Mergekit: A Cost-Effective Approach Using Small Language Models Simulating Ourselves and Our Societies With Generative Agents Synthetic Data for Anonymization, (..)

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Data Science AI Engineer Prompt Engineer Prompt Engineering 52

AWS Machine Learning Blog

MARCH 1, 2023

This blog post details the implementation of generative AI-assisted fashion online styling using text prompts. Machine learning (ML) engineers can fine-tune and deploy text-to-semantic-segmentation and in-painting models based on pre-trained CLIPSeq and Stable Diffusion with Amazon SageMaker.

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Generative AI AI AI Auto-classification 103

Heartbeat

OCTOBER 5, 2023

Unsurprisingly, Machine Learning (ML) has seen remarkable progress, revolutionizing industries and how we interact with technology. Where is LLMOps in DevOps and MLOps In MLOps, engineers are dedicated to enhancing the efficiency and impact of ML model deployment. The focus shifts towards prompt engineering and fine-tuning.

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Large Language Models DevOps Machine Learning Prompt Engineer 52

ODSC - Open Data Science

JANUARY 10, 2024

Takeaways include: The dangers of using post-hoc explainability methods as tools for decision-making, and where traditional ML falls short. Participants will walk away with a solid grasp of feature stores, equipped with the knowledge to drive meaningful insights and enhancements in their real-world ML platforms and projects.

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Large Language Models Deep Learning LLM Data Science 52

Snorkel AI

MAY 4, 2023

AI development stack: AutoML, ML frameworks, no-code/low-code development. 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. The free virtual conference is the largest annual gathering of the data-centric AI community.

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Computer Vision Large Language Models Natural Language Processing AI 52

Snorkel AI

MAY 4, 2023

AI development stack: AutoML, ML frameworks, no-code/low-code development. 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. The free virtual conference is the largest annual gathering of the data-centric AI community.

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Computer Vision Large Language Models Natural Language Processing AI 52

Snorkel AI

JUNE 9, 2023

Accelerate ML Adoption by Addressing Hidden Needs Max Williams, AI platform product manager at Wells Fargo , discussed the challenges of achieving a return on investment in machine learning as well as the hidden needs an organization must address for ML to gain widespread adoption and deliver attractive returns.

Large Language Models 52

Large Language Models Data Scientist Machine Learning Computer Vision 52

Snorkel AI

JUNE 9, 2023

Accelerate ML Adoption by Addressing Hidden Needs Max Williams, AI platform product manager at Wells Fargo , discussed the challenges of achieving a return on investment in machine learning as well as the hidden needs an organization must address for ML to gain widespread adoption and deliver attractive returns.

Large Language Models 52

Large Language Models Data Scientist Machine Learning Computer Vision 52

Heartbeat

JULY 17, 2023

Comet allows ML engineers to track these metrics in real-time and visualize their performance using interactive dashboards. We’re committed to supporting and inspiring developers and engineers from all walks of life. What comes out is amazing AI-generated art! We pay our contributors, and we don’t sell ads.

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Computer Vision Auto-classification Deep Learning Machine Learning 52

ODSC - Open Data Science

JANUARY 3, 2025

In this hands-on session, attendees will learn practical techniques like model testing across diverse scenarios, prompt engineering , hyperparameter optimization , fine-tuning , and benchmarking models in sandbox environments. Cloning NotebookLM with Open Weights Models Niels Bantilan, Chief ML Engineer atUnion.AI

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LLM AI AI Prompt Engineer 40

AWS Machine Learning Blog

MAY 9, 2024

The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. An effective approach that addresses a wide range of observed issues is the establishment of an AI/ML center of excellence (CoE). What is an AI/ML CoE?

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ML Generative AI AI AI 132

AWS Machine Learning Blog

SEPTEMBER 1, 2023

ML operationalization summary As defined in the post MLOps foundation roadmap for enterprises with Amazon SageMaker , ML and operations (MLOps) is the combination of people, processes, and technology to productionize machine learning (ML) solutions efficiently.

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Generative AI Prompt Engineer Prompt Engineering ML 126

AWS Machine Learning Blog

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

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AWS Machine Learning Blog

DECEMBER 17, 2024

Amazon SageMaker helps data scientists and machine learning (ML) engineers build FMs from scratch, evaluate and customize FMs with advanced techniques, and deploy FMs with fine-grain controls for generative AI use cases that have stringent requirements on accuracy, latency, and cost. Of the six challenges, the LLM met only one.

LLM 101

LLM Prompt Engineer Prompt Engineering Generative AI 101

AWS Machine Learning Blog

NOVEMBER 29, 2023

Amazon SageMaker MLOps lifecycle As the post “ MLOps foundation roadmap for enterprises with Amazon SageMaker ” describes, MLOps is the combination of processes, people, and technology to productionise ML use cases efficiently. input prompts comprising input data and query) and define metrics like similarity and toxicity.

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LLM Data Scientist Algorithm Generative AI 117

Marktechpost

NOVEMBER 14, 2024

Prior he was an ML product leader at Google working across products like Firebase, Google Research and the Google Assistant as well as Vertex AI. Dev’s academic background is in computer science and statistics, and he holds a masters in computer science from Harvard University focused on ML.

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Neural Network Deep Learning Machine Learning Generative AI 128