Machine Learning Optimization Software 
O'Reilly on Data
DECEMBER 10, 2019
Roughly a year ago, we wrote “ What machine learning means for software development.” In that article, we talked about Andrej Karpathy’s concept of Software 2.0. Karpathy argues that we’re at the beginning of a profound change in the way software is developed. Instead, we can program by example.
O'Reilly on Data
NOVEMBER 13, 2018
As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. We recently conducted a survey which garnered more than 11,000 respondents—our main goal was to ascertain how enterprises were using machine learning. Let’s begin by looking at the state of adoption.
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O'Reilly on Data
DECEMBER 19, 2018
In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure. Humans are still needed to write software, but that software is of a different type. Developers of Software 1.0
O'Reilly on Data
APRIL 2, 2019
Why companies are turning to specialized machine learning tools like MLflow. A few years ago, we started publishing articles (see “Related resources” at the end of this post) on the challenges facing data teams as they start taking on more machine learning (ML) projects. Image by Matei Zaharia; used with permission.
O'Reilly on Data
MAY 21, 2019
Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. I will highlight the results of a recent survey on machine learning adoption, and along the way describe recent trends in data and machine learning (ML) within companies.
O'Reilly on Data
JULY 15, 2019
As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. Machine learning developers are beginning to look at an even broader set of risk factors. Sources of model risk.
Smart Data Collective
NOVEMBER 1, 2021
Machine learning technology has become an integral part of many different design processes. Many entrepreneurs use machine learning to improve logo designs. One of the areas where machine learning has proven particularly useful has been with 3D printing. Optimize the Design. Use the Correct Materials.
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