Towards AI

AUGUST 25, 2023

Machine learning (ML) is a subset of AI that provides computer systems the ability to automatically learn and improve from experience without being explicitly programmed. In ML, there are a variety of algorithms that can help solve problems. Any competent software engineer can implement any algorithm. 12, 2014. [3]

Machine Learning 98

Machine Learning Software Engineer Neural Network Data Science 98

AWS Machine Learning Blog

APRIL 7, 2025

yml file from the AWS Deep Learning Containers GitHub repository, illustrating how the model synthesizes information across an entire repository. Codebase analysis with Llama 4 Using Llama 4 Scouts industry-leading context window, this section showcases its ability to deeply analyze expansive codebases. billion to a projected $574.78

Machine Learning 62

Machine Learning Large Language Models Python Automation 62

AWS Machine Learning Blog

NOVEMBER 16, 2023

Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.

Data Scientist 105

Data Scientist ML Data Science Machine Learning 105

TheSequence

JULY 12, 2023

After my post-doc I went to work for a string of small European startups before moving to the US in 2014 and joining Instacart where I led engineering teams dealing with payments and orders, and dabbled in MLOps. In 2018, I joined Cruise and cofounded the ML Infrastructure team there.

ML 97

ML Python Machine Learning Metadata 97

AWS Machine Learning Blog

JANUARY 25, 2023

Model explainability refers to the process of relating the prediction of a machine learning (ML) model to the input feature values of an instance in humanly understandable terms. Amazon SageMaker Clarify is a feature of Amazon SageMaker that enables data scientists and ML engineers to explain the predictions of their ML models.

Explainability 80

Explainability Algorithm Natural Language Processing Machine Learning 80

The MLOps Blog

JANUARY 30, 2025

See in app Full screen preview Check the documentation Play with an interactive example project Get in touch to go through a custom demo with our engineering team Cyclical cosine schedule Returning to a high learning rate after decaying to a minimum is not a new idea in machine learning.

LLM 64

LLM Machine Learning Large Language Models Deep Learning 64

Viso.ai

DECEMBER 21, 2023

Each of these individuals serves as an inspiration for aspiring AI and ML engineers breaking into the field. His contributions to ML, deep learning , computer vision, and NLP underscore his influence in the rapidly evolving AI landscape. We ranked these individuals in reverse chronological order.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52