FineReport

DECEMBER 19, 2019

When it comes to data analysis, from database operations, data cleaning, data visualization , to machine learning, batch processing, script writing, model optimization, and deep learning, all these functions can be implemented with Python, and different libraries are provided for you to choose. From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Data mining Reporting 98

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. It used deep learning to build an automated question answering system and a knowledge base based on that information.

Management 110

Management Machine Learning Experimentation Metrics 110

IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors.

Experimentation 73

Experimentation Deep Learning Modeling Data-driven 73

Cloudera

FEBRUARY 16, 2022

In this article, we explore model governance, a function of ML Operations (MLOps). We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI. The complete list is shown below: Model Lineage .

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

Occam's Razor

OCTOBER 12, 2017

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. I read articles they write. Intro to Machine Learning. Machine Learning. Deep Learning. This reality powers my impostor syndrome, and (yet?)

Marketing 138

Marketing Analytics Machine Learning Strategy 138

Ontotext

NOVEMBER 6, 2019

At the same time, the community there is of users can share the best practices, enabling the cross-pollination of the most successful and most fruitful results of their experimentation. It also enables Ontotext to develop specific functionality as plugins without having to fiddle with the core functionality of the database. The Plugins.

Experimentation 45

Experimentation Deep Learning Software Modeling 45

IBM Big Data Hub

APRIL 18, 2024

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production. It analyzes historical data and news articles, confirming a possible market correction.

Cost-Benefit 89

Cost-Benefit Manufacturing Modeling Interactive 89

O'Reilly on Data

JULY 28, 2020

In this article, we turn our attention to the process itself: how do you bring a product to market? Without clarity in metrics, it’s impossible to do meaningful experimentation. Experimentation should show you how your customers use your site, and whether a recommendation engine would help the business. Identifying the problem.

Marketing 364

Marketing Experimentation Metrics Testing 364

O'Reilly on Data

MARCH 19, 2020

Our analysis of ML- and AI-related data from the O’Reilly online learning platform indicates: Unsupervised learning surged in 2019, with usage up by 172%. Deep learning cooled slightly in 2019, slipping 10% relative to 2018, but deep learning still accounted for 22% of all AI/ML usage.

Deep Learning 357

Deep Learning Machine Learning Data-driven Modeling 357

Data Science and Beyond

DECEMBER 23, 2018

In my opinion it’s more exciting and relevant to everyday life than more hyped data science areas like deep learning. However, I’ve found it hard to apply what I’ve learned about causal inference to my work. I’ve been interested in the area of causal inference in the past few years.

Deep Learning 103

Deep Learning Experimentation Data Science Data-driven 103

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Introduction. Welcome back to our monthly burst of themes and conferences.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

CIO Business Intelligence

MAY 6, 2025

These capabilities are no longer theoretical or experimental. While the algorithms can vary in complexity, from logistic regression to deep learning, the value lies in what they help us anticipate and prevent. This article was made possible by our partnership with the IASA Chief Architect Forum. Want to join?

Prescriptive Analytics 78

Prescriptive Analytics Predictive Analytics Descriptive Analytics ROI 78