O'Reilly on Data

MARCH 19, 2020

Deep learning cooled slightly in 2019, slipping 10% relative to 2018, but deep learning still accounted for 22% of all AI/ML usage. PyTorch looks like a contender: it posted triple-digit growth in usage share rates in both 2018 and 2019. For example, the chatbots topic continues to decline, first by 17% in 2018 and by 34% in 2019.

Deep Learning 276

Deep Learning Machine Learning Data-driven Modeling 276

CIO Business Intelligence

JUNE 15, 2023

A lot has happened since that last survey on attitudes to AI in 2018. It’s important folks get a chance to interact with these technologies and use them; stopping experimentation is not the answer,” Mills said, noting that it’s also not practical. “AI

Management 116

Management Experimentation Optimization Enterprise 116

The Unofficial Google Data Science Blog

APRIL 23, 2024

To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. However, if we experiment with both parameters at the same time we will learn something about interactions between these system parameters.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Corinium

JUNE 6, 2019

It is also important to have a strong test and learn culture to encourage rapid experimentation. Newer methods can work with large amounts of data and are able to unearth latent interactions. One approach is to use NLP techniques to analyze actual call center interactions with customers.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Business Over Broadway

MAY 22, 2019

For those of you who are interested, here is Gartner’s latest (2018) hype cycle on emerging technologies. According to Gartner, companies need to adopt these practices: build culture of collaboration and experimentation; start with a 3-way partnership among executives leading digital initiative, line of business and IT.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

Data Science and Beyond

JULY 22, 2018

This article is a short summary of my understanding of the definition of data science in 2018. No one is born an expert – expertise is gained by learning from and interacting with the world. Even better – I still get paid for being a data scientist. But what does it mean? What do I actually do here?

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

Domino Data Lab

JULY 2, 2019

AutoPandas was created at UC Berkeley RISElab and the general idea is described in the NeurIPS 2018 paper “ Neural Inference of API Functions from Input–Output Examples ” by Rohan Bavishi, Caroline Lemieux, Neel Kant, Roy Fox, Koushik Sen, and Ion Stoica. Program Synthesis Papers at ICLR 2018 ” – Illia Polosukhin (2018-05-01).

Metadata 105

Metadata Machine Learning Data Science Data-driven 105