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

Decision Management Solutions

FEBRUARY 8, 2021

The goal is to establish the Mayflower 400 as an open platform for marine research that would reduce costs and ease the burden on scientists and sailors, who have to brave a dangerous and unpredictable environment in the course of their data-collecting missions. We’re finding that it doesn’t have to be completely autonomous.

Machine Learning 93

Machine Learning Testing Deep Learning Optimization 93

O'Reilly on Data

JUNE 18, 2019

Even if we boosted the quality of the available data via unification and cleaning, it still might not be enough to power the even more complex analytics and predictions models (often built as a deep learning model). An important paradigm for solving both these problems is the concept of data programming.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

IBM Big Data Hub

SEPTEMBER 6, 2023

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. What is AI marketing?

Marketing 83

Marketing Technology Advertising ROI 83

DataRobot Blog

JULY 27, 2022

Here we will demonstrate an end-to-end unattended workflow that: trains a new model on the Fashion MNIST Dataset uploads it to an Algorithmia Data Collection creates a new algorithm on Algorithmia creates DataRobot deployment Links everything together via the MLOps Agent. The Demo: Autoscaling with MLOps.

Metrics 52

Metrics Deep Learning Modeling Machine Learning 52

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

Cloudera

NOVEMBER 19, 2020

The Public Sector data challenge. Robust online systems have streamlined interactions and generated a wealth of new data to support mission success and enhanced citizen engagements. However, this rapid scaling up of data across government agencies brings with it new challenges. Modernization has been a boon to government.

Machine Learning 114

Machine Learning Data-driven Modeling Deep Learning 114

Domino Data Lab

JULY 22, 2019

By virtue of that, if you take those log files of customers interactions, you aggregate them, then you take that aggregated data, run machine learning models on them, you can produce data products that you feed back into your web apps, and then you get this kind of effect in business. You can take TensorFlow.js

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Machine learning model interpretability. training data”) show the tangible outcomes.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

JUNE 23, 2019

This talk will describe how you can navigate all these challenges that you’re going to face and build a business where every product interaction benefits from your investment in machine learning. 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

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Methods for explaining Deep Learning.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

O'Reilly on Data

MARCH 24, 2020

Beyond the autonomous driving example described, the “garbage in” side of the equation can take many forms—for example, incorrectly entered data, poorly packaged data, and data collected incorrectly, more of which we’ll address below. The model and the data specification become more important than the code.

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346