Towards AI

JUNE 18, 2024

About Building LLMs for Production Generative AI and LLMs are transforming industries with their ability to understand and generate human-like text and images. However, building reliable and scalable LLM applications requires a lot of extra work and a deep understanding of various techniques and frameworks.

Large Language Models 79

Large Language Models Prompt Engineer Prompt Engineering LLM 79

AWS Machine Learning Blog

NOVEMBER 30, 2023

Solution overview In the following sections, we share how you can develop an example ML project with Code Editor on Amazon SageMaker Studio. We will deploy a Mistral-7B large language model (LLM) model into an Amazon SageMaker real-time endpoint using a built-in container from HuggingFace.

Machine Learning 119

Machine Learning ML LLM Python 119

ODSC - Open Data Science

FEBRUARY 25, 2025

Topics Include: Agentic AI DesignPatterns LLMs & RAG forAgents Agent Architectures &Chaining Evaluating AI Agent Performance Building with LangChain and LlamaIndex Real-World Applications of Autonomous Agents Who Should Attend: Data Scientists, Developers, AI Architects, and ML Engineers seeking to build cutting-edge autonomous systems.

Data Scientist 52

Data Scientist Machine Learning Large Language Models ML Engineer 52

AWS Machine Learning Blog

OCTOBER 22, 2024

Data scientists and machine learning (ML) engineers use pipelines for tasks such as continuous fine-tuning of large language models (LLMs) and scheduled notebook job workflows. Create a complete AI/ML pipeline for fine-tuning an LLM using drag-and-drop functionality. But fine-tuning an LLM just once isn’t enough.

Automation 79

Automation LLM DevOps Python 79

ODSC - Open Data Science

FEBRUARY 21, 2025

AI Agents AI Software Engineering Agents: What Works and WhatDoesnt Robert Brennan | CEO | All HandsAI AI is reshaping software development, but are autonomous coding agents like Devin and OpenHands a game-changer or just hype? These luminaries come from the companies and institutions at the forefront of innovation.

Data Scientist 52

Data Scientist Software Engineer LLM Neural Network 52

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. Instead, Twain employs linguists and salespeople as prompt engineers.

Prompt Engineering 59

Prompt Engineering Prompt Engineer Generative AI Large Language Models 59

AWS Machine Learning Blog

OCTOBER 19, 2023

This makes Amazon Comprehend particularly helpful for redacting PII from unstructured text that may contain a mix of PII and non-PII words (for example, support tickets or LLM prompts) that is stored in a tabular format. Amazon SageMaker provides purpose-built tools for ML teams to automate and standardize processes across the ML lifecycle.

Machine Learning 104

Machine Learning Python ML Automation 104

AWS Machine Learning Blog

FEBRUARY 5, 2024

SageMaker geospatial capabilities make it easy for data scientists and machine learning (ML) engineers to build, train, and deploy models using geospatial data. With over 15 years of experience, he supports customers globally in leveraging AI and ML for innovative solutions that capitalize on geospatial data.

ML 99

ML Machine Learning Python Software Engineer 99

Mlearning.ai

AUGUST 18, 2023

As a software engineer your role is to write code for a certain cause. As a software developer the more versed you are in DevOps the better you can foresee issues, fix bugs and be a valued team member. As an ML engineer you’re in charge of some code/model. Same analogy applies to MLOps.

DevOps 52

DevOps Python ML ML Engineer 52

The MLOps Blog

JUNE 27, 2023

Collaborative workflows : Dataset storage and versioning tools should support collaborative workflows, allowing multiple users to access and contribute to datasets simultaneously, ensuring efficient collaboration among ML engineers, data scientists, and other stakeholders. LLM training configurations.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

JULY 23, 2024

collection of multilingual large language models (LLMs), which includes pre-trained and instruction tuned generative AI models in 8B, 70B, and 405B sizes, is available through Amazon SageMaker JumpStart to deploy for inference. Architecturally, the core LLM for Llama 3 and Llama 3.1 models using SageMaker JumpStart.

Machine Learning 115

Machine Learning Computer Vision Python ML 115

AWS Machine Learning Blog

DECEMBER 4, 2024

This integration addresses these hurdles by providing data scientists and ML engineers with a comprehensive environment that supports the entire ML lifecycle, from development to deployment at scale. In this post, we walk you through the process of scaling your ML workloads using SageMaker Studio and SageMaker HyperPod.

ML 93

ML Data Scientist Software Engineer Large Language Models 93

ODSC - Open Data Science

MARCH 11, 2025

The second script shows how to query those embeddings with an LLM for RAG-based Q&A. This quick workflow lets you maintain a powerful, scalable knowledge base for any LLM-powered application. The first script ingests text data, chunks it, creates embeddings, and writes them to Neo4j. This is for demonstration purposesonly! .")

LLM 52

LLM Metadata Software Engineer Python 52