AWS Machine Learning Blog

NOVEMBER 14, 2024

It includes processes for monitoring model performance, managing risks, ensuring data quality, and maintaining transparency and accountability throughout the model’s lifecycle. Model risk : Risk categorization of the model version. Keshav Chandak is a Software Engineer at AWS with a focus on the SageMaker Repository Service.

ML 89

ML Machine Learning Auto-complete Auto-classification 89

Towards AI

MAY 20, 2023

Challenges of building custom LLMs Building custom Large Language Models (LLMs) presents an array of challenges to organizations that can be broadly categorized under data, technical, ethical, and resource-related issues. Ensuring data quality during collection is also important.

LLM 98

LLM Large Language Models Chatbots Natural Language Processing 98

ODSC - Open Data Science

FEBRUARY 11, 2025

While machine learning engineers focus on building models, AI engineers often work with pre-trained foundation models, adapting them to specific use cases. This shift has made AI engineering more multidisciplinary, incorporating elements of data science, software engineering, and systemdesign.

AI Engineer 52

AI Engineer Machine Learning Software Engineer Prompt Engineer 52

Snorkel AI

FEBRUARY 2, 2023

Scenario: Entity linking with payroll data and job classifications I’m building an entity-linking app to connect job listings in a payroll system to a job categorization system developed by the Bureau of Labor Statistics. I thumb through the data and look for patterns. We’ll start with a simple logistic regression model.

Auto-classification 52

Auto-classification Software Engineer Neural Network Machine Learning 52

Snorkel AI

FEBRUARY 2, 2023

Scenario: Entity linking with payroll data and job classifications I’m building an entity-linking app to connect job listings in a payroll system to a job categorization system developed by the Bureau of Labor Statistics. I thumb through the data and look for patterns. We’ll start with a simple logistic regression model.

Auto-classification 52

Auto-classification Software Engineer Neural Network Machine Learning 52

Pickl AI

NOVEMBER 28, 2024

Data Transformation Transforming data prepares it for Machine Learning models. Encoding categorical variables converts non-numeric data into a usable format for ML models, often using techniques like one-hot encoding. This includes scaling numerical values, especially when models are sensitive to feature magnitudes.

Machine Learning 52

Machine Learning Neural Network ML Engineer Algorithm 52