IBM Big Data Hub

OCTOBER 4, 2022

Today, AI presents an enormous opportunity to turn data into insights and actions, to amplify human capabilities, decrease risk and increase ROI by achieving break through innovations. Furthermore, 59% of executives claim AI can improve the use of big data in their organizations, facts about artificial intelligence show. (

Metadata 102

Metadata Risk Risk Management Experimentation 102

Domino Data Lab

NOVEMBER 14, 2019

This Domino Data Science Field Note covers a proposed definition of interpretability and distilled overview of the PDR framework. Model interpretability continues to spark public discourse among industry. Model interpretability continues to spark public discourse among industry. Insights are drawn from Bin Yu, W.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

Cloudera

OCTOBER 14, 2020

alone, average about 45,000 daily flights and transporting over 10 million passengers a year (source: FAA ). Not many other industries have such a sophisticated business model that encompasses a culture of streamlined supply chains, predictive maintenance, and unwavering customer satisfaction. Airlines, in just the U.S. The Process.

Machine Learning 97

Machine Learning Modeling Cost-Benefit Testing 97

Sisense

OCTOBER 29, 2020

We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. It’s difficult not to get excited about this future.

Machine Learning 90

Machine Learning Data Collection Cost-Benefit Advertising 90

Sisense

AUGUST 14, 2020

In Augmented Apps , we examine how product teams are exploring AI and Machine Learning to make their products more intuitive and enhance the user experience. . Certain proven methods and use cases are invaluable in helping product teams understand how to implement AI in apps to reproduce and enhance existing successes.

Machine Learning 98

Machine Learning Visualization Predictive Analytics Testing 98

Insight

MARCH 27, 2019

DeepAugment is an AutoML tool focusing on data augmentation. It utilizes Bayesian optimization for discovering data augmentation strategies tailored to your image dataset. To learn more about how I built this, read on! Introduction Data is the most critical piece of AI applications.

Optimization 75

Optimization Cost-Benefit Modeling Strategy 75

O'Reilly on Data

OCTOBER 13, 2020

Our previous articles in this series introduce our own take on AI product management , discuss the skills that AI product managers need , and detail how to bring an AI product to market. Another, of course, is to ensure that the product functions as expected and desired over time.

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Management Metrics Machine Learning Modeling 246

O'Reilly on Data

NOVEMBER 28, 2023

And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. Our survey focused on how companies use generative AI, what bottlenecks they see in adoption, and what skills gaps need to be addressed.

Enterprise 273

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IBM Big Data Hub

JULY 6, 2023

These computer science terms are often used interchangeably, but what differences make each a unique technology? 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.

Deep Learning 62

Deep Learning Machine Learning Unstructured Data Modeling 62

Sisense

AUGUST 6, 2020

In Augmented Apps , we examine how product teams are exploring AI and ML to make their products more intuitive and enhance the user experience. AI and machine learning (ML) are not just catchy buzzwords; they’re vital to the future of our planet and your business. Improving performance with AI.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

DataRobot Blog

DECEMBER 15, 2022

Working from datasets you already have, a Time Series Forecasting model can help you better understand seasonality and cyclical behavior and make future-facing decisions, such as reducing inventory or staff planning. Let’s run through the process and see exactly how you can go from data to predictions.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

Sisense

SEPTEMBER 25, 2020

A data scientist must be skilled in many arts: math and statistics, computer science, and domain knowledge. A data scientist must be skilled in many arts: math and statistics, computer science, and domain knowledge. In this article, we will explain how to execute five statistical techniques using Python.

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Machine Learning 79

Machine Learning Manufacturing Cost-Benefit Deep Learning 79

AWS Big Data

SEPTEMBER 29, 2023

In today’s digital age, data is at the heart of every organization’s success. One of the most commonly used formats for exchanging data is XML. Analyzing XML files can help organizations gain insights into their data, allowing them to make better decisions and improve their operations.

Metadata 65

Metadata Visualization Data-driven Optimization 65

AWS Big Data

JUNE 21, 2023

In recent years, machine learning (ML) techniques have become increasingly popular to enhance search. An embedding model, for instance, could encode the semantics of a corpus. An embedding model, for instance, could encode the semantics of a corpus. You go to Amazon.com, and you type “a cozy place to sit by the fire.”

Metrics 78

Metrics Measurement Modeling Dashboards 78

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Domino Data Lab

MAY 20, 2021

In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed. Further, imbalanced data exacerbates problems arising from the curse of dimensionality often found in such biological data. This renders measures like classification accuracy meaningless.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Sisense

OCTOBER 14, 2020

Here, we focus on the role of the data team in successfully applying advanced analytics and ensuring that you get the most from your data to make your organization truly data-driven. Smart organizations already appreciate the power of data and its influence on building successful strategies. Why build your data team?

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Data-driven Machine Learning Dashboards Sales 98

The Unofficial Google Data Science Blog

JULY 18, 2023

by MICHAEL QUINN, JEREMY MILES, KA WONG As data scientists, we often encounter situations in which human judgment provides the ground truth. How do we think about the quality of human ratings, and how do we quantify our understanding is the subject of this post. Some of this data is human-labeled.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

Domino Data Lab

MARCH 6, 2019

Niels Kasch , cofounder of Miner & Kasch , an AI and Data Science consulting firm, provides insight from a deep learning session that occurred at the Maryland Data Science Conference. Outlook, with Justin Leto, Big Data & AI: State of the Industry, Labor Trends and Future Outlook. Introduction.

Deep Learning 55

Deep Learning Data Science Machine Learning Modeling 55

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. ln this post he describes where and how having “humans in the loop” in forecasting makes sense, and reflects on past failures and successes that have led him to this perspective.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Insight

MARCH 18, 2019

Bias in Machine Learning Algorithms (Bottom Photos Source: ProPublica ; Top Photos Source: Pexels.com) Biases in predictive modeling are a widespread issue Machine learning and AI applications are used across industries, from recommendation engines to self-driving cars and more. These groups have an automatic boost built-in.

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Machine Learning Predictive Modeling Modeling Metrics 77