AWS Big Data

OCTOBER 26, 2023

Some recent examples of performance optimizations driven by fleet telemetry include: String query optimizations – By analyzing how Amazon Redshift processed different data types in the Redshift fleet, we found that optimizing string-heavy queries would bring significant benefit to our customers’ workloads.

Data Warehouse 95

Data Warehouse Cost-Benefit Dashboards Optimization 95

Smarten

APRIL 19, 2024

Benefits include customized and optimized models, data, parameters and tuning. Price and bundling optimization, demand pricing, and other variables will be included to provide the best options, prices and responses and to personalize the approach and present results for data analysis and for end users.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

IBM Big Data Hub

APRIL 18, 2024

Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move. Also, its emotional intelligence allows it to adapt communication to be empathetic and supportive, creating a more positive interaction for the customer.

Cost-Benefit 97

Cost-Benefit Modeling Manufacturing Interactive 97

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

For example, consider the following simple example fitting a two-dimensional function to predict if someone will pass the bar exam based just on their GPA (grades) and LSAT (a standardized test) using the public dataset (Wightman, 1998). Curiosities and anomalies in your training and testing data become genuine and sustained loss patterns.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Cloudera

NOVEMBER 3, 2021

Thanks to pioneers like Andrew NG and Fei-Fei Li, GPUs have made headlines for performing particularly well with deep learning techniques. Today, deep learning and GPUs are practically synonymous. While deep learning is an excellent use of the processing power of a graphics card, it is not the only use.

Deep Learning 116

Deep Learning Machine Learning Data Science Cost-Benefit 116

Decision Management Solutions

FEBRUARY 8, 2021

As you’ll see, the development of this amazing, one-of-a-kind vessel led to a conclusion that we at Decision Management Solutions see every day in our client work: It’s never enough to just rely on artificial intelligence (AI)/machine learning (ML) to do all the decision-making. Marine AI—based in Plymouth, U.K.—in

Machine Learning 93

Machine Learning Testing Deep Learning Optimization 93

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

IBM Big Data Hub

SEPTEMBER 6, 2023

Once trained, these bots can interact with customers no matter where they are on their customer journey, help resolve tickets quickly and effectively and increase customer satisfaction. AI can help marketers create and optimize content to meet the new standards.

Marketing 87

Marketing Technology Advertising ROI 87

DataRobot

OCTOBER 20, 2021

Individuals interacting with AI systems should possess a baseline data literacy, especially in high-risk use cases that require human collaboration at the final decision-making stage. rule-based AI , machine learning , deep learning , etc.) WHITE PAPER. Data Literacy for Responsible AI. Download Now.

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52

Domino Data Lab

JULY 28, 2021

It is the job of a data scientist to navigate these subtle differences, pick the model that aligns best with the problem statement, optimize and monitor performance and translate the findings back into a business context. After thorough review, revision, possible unit-testing, code reviews and the greenlight from any relevant stakeholders.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

O'Reilly on Data

JANUARY 25, 2021

We’ve explored usage across all publishing partners and learning modes, from live training courses and online events to interactive functionality provided by Katacoda and Jupyter notebooks. It’s particularly difficult if testing includes issues like fairness and bias.

Machine Learning 363

Machine Learning Software Testing Technology 363

CIO Business Intelligence

APRIL 4, 2022

If a specific email or login credential is identified in a potentially fraudulent transaction, all future interactions with this email or credential can be subject to additional scrutiny. Find out more and take a test drive in one of Dell Technologies’ worldwide Customer Solution Centers. Real-time Fraud Detection.

Technology 52

Technology Deep Learning Cost-Benefit Data Quality 52

Insight

APRIL 9, 2019

For industries outside of tech, ML can be utilized to personalize a user’s experience, automate laborious tasks and optimize subjective decision making. The biggest categories of cost for hardware designers and manufacturers are testing, verification, and calibration of their control systems. It is far from an automated process.

Manufacturing 75

Manufacturing Machine Learning Testing Software 75

Domino Data Lab

JULY 2, 2019

SQL optimization provides helpful analogies, given how SQL queries get translated into query graphs internally , then the real smarts of a SQL engine work over that graph. Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning. Software writes Software?

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

IBM Big Data Hub

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

Deep Learning 63

Deep Learning Machine Learning Unstructured Data Modeling 63

Domino Data Lab

JULY 28, 2021

Today, data is generated constantly through multiple channels including transactional systems, sensors, cameras, and online interactions. In fact, deep learning was first described theoretically in 1943. Reinforcement learning focuses on optimizing a specific decision. None of these techniques are new.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

Domino Data Lab

MARCH 29, 2021

Some of the key benefits of using Spark for machine learning include: Distributed Learning – Parallelize compute-heavy workloads such as distributed training or hyper-parameter tuning Interactive Exploratory Analysis – Efficiently load large data sets in a distributed manner. GPU) and use bitnami/spark:2.4.6

Cost-Benefit 98

Cost-Benefit Machine Learning Testing Interactive 98

Cloudera

SEPTEMBER 12, 2018

Commonwealth Bank of Australia worked with Cloudera to implement a modern data platform with an AI-powered customer decisioning layer that dramatically improves how the bank interacts with its customers. The bank brought together 27 billion data points and uses AI to understand the next-best conversation 21 million times each weekday.

Machine Learning 44

Machine Learning Big Data Data Science Data Warehouse 44

Domino Data Lab

MAY 8, 2019

For example, in the case of more recent deep learning work, a complete explanation might be possible: it might also entail an incomprehensible number of parameters. Agile was originally about iterating fast on a code base and its unit tests, then getting results in front of stakeholders. Generally, you cannot get both.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

O'Reilly on Data

JUNE 7, 2022

We have a lot of vague notions about the Turing test, but in the final analysis, Turing wasn’t offering a definition of machine intelligence; he was probing the question of what human intelligence means. And granted, a lot can be done to optimize training (and DeepMind has done a lot of work on models that require less energy).

Modeling 363

Modeling Interactive Optimization Deep Learning 363

Domino Data Lab

JULY 9, 2019

A “data scientist” might build a multistage processing pipeline in Python, design a hypothesis test, perform a regression analysis over data samples with R, design and implement an algorithm in Hadoop, or communicate the results of our analyses to other members of the organization in a clear and concise fashion.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Domino Data Lab

JUNE 23, 2019

Be aware that machine learning often involves working on something that isn’t guaranteed to work. As a result, Skomoroch advocates getting “designers and data scientists, machine learning folks together and using real data and prototyping and testing” as quickly as possible. Testing is critical. It is similar to R&D.

Management 110

Management Machine Learning Experimentation Metrics 110

Alation

APRIL 14, 2022

Supports the ability to interact with the actual data and perform analysis on it. Automatic sampling to test transformation. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. A technique to automate changes in iterative passes. Pattern Matching.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

DataRobot Blog

DECEMBER 20, 2022

In this context, an augmented intelligence approach around the data will be increasingly more critical for asset managers, investors, and real estate developers to ensure a better understanding of the real estate assets and take better decisions aimed at optimizing both the Net Asset Value and the Net Operating Income.

Management 59

Management Machine Learning Optimization Modeling 59