Occam's Razor

MARCH 30, 2017

People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Most Deep Learning methods involve artificial neural networks, modeling how our bran works. There won’t be any need for them.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

IBM Big Data Hub

FEBRUARY 23, 2024

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. DL models can improve over time through further training and exposure to more data. These technologies enable systems to interact, learn from interactions, adapt and become more efficient.

Enterprise 100

Enterprise Interactive Data-driven Key Performance Indicator 100

DataRobot Blog

JULY 27, 2022

In this technical post, we’ll focus on some changes we’ve made to allow custom models to operate as an algorithm on Algorithmia, while still feeding predictions, input, and other metrics back to the DataRobot MLOps platform —a true best of both worlds. Data Science Expertise Meets Scalability. Then select, Create new key.

Metrics 52

Metrics Deep Learning Modeling Machine Learning 52

IBM Big Data Hub

FEBRUARY 14, 2024

Other uses include Netflix offering viewing recommendations powered by models that process data sets collected from viewing history; LinkedIn uses ML to filter items in a newsfeed, making employment recommendations and suggestions on who to connect with; and Spotify uses ML models to generate its song recommendations.

Cost-Benefit 85

Cost-Benefit Insurance Unstructured Data Machine Learning 85

Ontotext

DECEMBER 15, 2023

It includes only ML papers and related entities; this SPARQL query shows some statistics: papers tasks models datasets methods evaluations repos 376557 4267 24598 8322 2101 52519 153476 We can start with these repositories (most of them are on Github) and get all their topics. We can start with a connecting dataset like LinkedPapersWithCode.

Machine Learning 69

Machine Learning Interactive Deep Learning Statistics 69

Insight

JANUARY 14, 2020

a “pre-trained” model) to be recycled and reused for many different tasks. In short, I was faced with two major difficulties regarding data collection: I didn’t have nearly enough images, and the images I did have were not representative of a realistic gym environment. This structure allows the same network (i.e.

Metrics 58

Metrics Optimization Modeling Testing 58

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. This blog post provides a concise session summary, a video, and a written transcript. data science’s emergence as an interdisciplinary field – from industry, not academia. The data governance parts of it have become more and more important.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

IBM Big Data Hub

NOVEMBER 14, 2023

But few organizations have made the strategic shift to managing “data as a product.” ” This data management means applying product development practices to data. Each data product has its own lifecycle environment where its data and AI assets are managed in their product-specific data lakehouse.

Strategy 108

Strategy Cost-Benefit Data-driven Measurement 108

Cloudera

NOVEMBER 19, 2020

Machine learning algorithms enable fraud detection systems to distinguish between legitimate and fraudulent behaviors. Some of these algorithms can be adaptive to quickly update the model to take into account new, previously unseen fraud tactics allowing for dynamic rule adjustment. The Public Sector data challenge.

Machine Learning 114

Machine Learning Data-driven Modeling Deep Learning 114

IBM Big Data Hub

MAY 17, 2023

They use drones for tasks as simple as aerial photography or as complex as sophisticated data collection and processing. It can offer data on demand to different business units within an organization, with the help of various sensors and payloads. The global commercial drone market is projected to grow from USD 8.15

Data Collection 80

Data Collection Visualization Data-driven Unstructured Data 80

Cloudera

OCTOBER 1, 2022

While the word “data” has been common since the 1940s, managing data’s growth, current use, and regulation is a relatively new frontier. . Governments and enterprises are working hard today to figure out the structures and regulations needed around data collection and use.

Data Governance 71

Data Governance Strategy Enterprise Machine Learning 71

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. Machine learning model interpretability. Introduction.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

datapine

NOVEMBER 19, 2019

An important part of artificial intelligence comprises machine learning, and more specifically deep learning – that trend promises more powerful and fast machine learning. An exemplary application of this trend would be Artificial Neural Networks (ANN) – the predictive analytics method of analyzing data.

Technology 279

Technology Internet of Things IT IoT 279

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

O'Reilly on Data

MARCH 24, 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. The model and the data specification become more important than the code.

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346

Occam's Razor

OCTOBER 12, 2017

Like this blog, it will be particularly relevant for those who are in digital analytics and digital marketing. Intro to Machine Learning. Machine Learning. Deep Learning. Collect a handful of the smartest people you know, draw a box on a whiteboard, have a discussion. All three of these courses are free: 1.

Marketing 136

Marketing Analytics Machine Learning Strategy 136