O'Reilly on Data

MARCH 18, 2020

The new survey, which ran for a few weeks in December 2019, generated an enthusiastic 1,388 responses. Supervised learning is the most popular ML technique among mature AI adopters, while deep learning is the most popular technique among organizations that are still evaluating AI. But what kind?

Enterprise 349

Enterprise Deep Learning Data Governance Risk 349

Corinium

JUNE 6, 2019

It is also important to have a strong test and learn culture to encourage rapid experimentation. A playbook for this is to run multiple experiments in parallel and create ‘MVPs’ (fail/learn fast), as well as incorporate feedback mechanisms to enable an improvement loop, and scaling the ones that show the fastest path to ROI.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

O'Reilly on Data

MARCH 31, 2020

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. Managing Machine Learning Projects” (AWS). People + AI Guidebook” (Google).

Management 363

Management Machine Learning Experimentation Metrics 363

DataKitchen

APRIL 13, 2021

ParallelM — Moves machine learning into production, automates orchestration, and manages the ML pipeline. Acquired by DataRobot June 2019). Metis Machine — Enterprise-scale Machine Learning and Deep Learning deployment and automation platform for rapid deployment of models into existing infrastructure and applications.

Testing 300

Testing Machine Learning Consulting Data Science 300

CIO Business Intelligence

APRIL 25, 2023

A transformer is a type of AI deep learning model that was first introduced by Google in a research paper in 2017. ChatGPT was trained with 175 billion parameters; for comparison, GPT-2 was 1.5B (2019), Google’s LaMBDA was 137B (2021), and Google’s BERT was 0.3B (2018). What is ChatGPT? ChatGPT is a product of OpenAI.

Experimentation 116

Experimentation Deep Learning Enterprise Modeling 116

KDnuggets

NOVEMBER 19, 2019

Find out how data scientists and AI practitioners can use a machine learning experimentation platform like Comet.ml to apply machine learning and deep learning to methods in the domain of audio analysis.

Deep Learning 52

Deep Learning Machine Learning Experimentation 52

Domino Data Lab

JULY 2, 2019

See also: Caroline Lemieux’s slides for that NeurIPS talk, and Rohan Bavishi’s video from the RISE Summer Retreat 2019. The authors of AutoPandas observed that: The APIs for popular data science packages tend to have relatively steep learning curves. Program Synthesis 101 ” – Alexander Vidiborskiy (2019-01-20).

Metadata 105

Metadata Data Science Machine Learning Data-driven 105