O'Reilly on Data

NOVEMBER 25, 2019

In this interview from O’Reilly Foo Camp 2019, Dean Wampler, head of evangelism at Anyscale.io, talks about moving AI and machine learning into real-time production environments. In some cases, AI and machine learning technologies are being used to improve existing processes, rather than solving new problems.

Machine Learning 327

Machine Learning Modeling Technology IT 327

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. We won’t go into the mathematics or engineering of modern machine learning here.

Management 363

Management Machine Learning Experimentation Metrics 363

KDnuggets

AUGUST 14, 2019

At times it may seem Machine Learning can be done these days without a sound statistical background but those people are not really understanding the different nuances. Code written to make it easier does not negate the need for an in-depth understanding of the problem.

Machine Learning 123

Machine Learning Statistics Modeling IT 123

KDnuggets

OCTOBER 17, 2019

This post aims to make you get started with putting your trained machine learning models into production using Flask API.

Machine Learning 122

Machine Learning Modeling 122

O'Reilly on Data

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. Growth is still strong for such a large topic, but usage slowed in 2018 (+13%) and cooled significantly in 2019, growing by just 7%.

Data-driven 363

Data-driven Software Statistics Marketing 363

Smart Data Collective

OCTOBER 13, 2021

It’s similar to prices – price optimization through machine learning is a great tool to grow your revenue. What can you learn from real-market examples? Figuring out the best pricing model can be tricky. That’s where machine learning algorithms come into place. How exactly? What product generates more money?

Machine Learning 137

Machine Learning Optimization Software Marketing 137

O'Reilly on Data

NOVEMBER 13, 2019

In this interview from O’Reilly Foo Camp 2019, Eric Jonas, assistant professor at the University of Chicago, pierces the hype around artificial intelligence. Questions of ethics and what role it should play are increasingly arising in machine learning and AI research, especially in the area of science applications.

Machine Learning 284

Machine Learning Data Collection Modeling IT 284

KDnuggets

SEPTEMBER 27, 2019

This live webinar, Oct 2 2019, will instruct data scientists and machine learning engineers how to build manage and deploy auto-adaptive machine learning models in production. Save your spot now.

Machine Learning 94

Machine Learning Modeling Management 94

KDnuggets

OCTOBER 14, 2019

Selecting the perfect machine learning model is part art and part science. Learn how to review multiple models and pick the best in both competitive and real-world applications.

Machine Learning 95

Machine Learning Modeling 95

Smart Data Collective

JUNE 3, 2021

Many different industries are becoming more reliant on machine learning. The insurance industry is among those that has found new opportunities to take advantage of machine learning technology. Many of the applications of big data for insurance companies will be realized with machine learning technology.

Insurance 123

Insurance Machine Learning Cost-Benefit Risk 123

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. . Meta-Orchestration .

Testing 304

Testing Machine Learning Consulting Data Science 304

KDnuggets

SEPTEMBER 4, 2019

In the following post, I am going to give a brief guide to four of the most established packages for interpreting and explaining machine learning models.

Machine Learning 123

Machine Learning Modeling 123

KDnuggets

SEPTEMBER 13, 2019

I am a Git god, why do I need another version control system for Machine Learning Projects?

Machine Learning 118

Machine Learning Data Science Modeling 118

Business Over Broadway

JULY 22, 2020

Top tools for automation were related to model selection and data augmentation. Machine learning is employed by data scientists to find patterns and predict important outcomes. The application of machine learning reaches across industries (e.g., Most Used Machine Learning Algorithms. TensorFlow (39%).

Machine Learning 104

Machine Learning Data Science Modeling Marketing 104

Smart Data Collective

FEBRUARY 4, 2021

Machine learning is among the biggest disruptive technologies to ever impact the field of online commerce. What changes can many brands in the e-commerce sector expect to witness from new developments in big data and machine learning ? In 2019, over 1.9 This is the biggest advantage for new e-commerce companies.

Machine Learning 111

Machine Learning Sales Big Data Data-driven 111

KDnuggets

NOVEMBER 6, 2019

This guide explores research centered on a variety of advanced loss functions for machine learning models.

Machine Learning 97

Machine Learning Modeling 97

Data Science 101

JUNE 3, 2019

Cloud Programming Simplified: A Berkeley View on Serverless Computing (2019) – Serverless computing is very popular nowadays and this article covers some of the limitations.

Data Science 96

Data Science Machine Learning Modeling Software 96

KDnuggets

AUGUST 27, 2019

Recently, AI researchers from IBM open sourced AI Explainability 360, a new toolkit of state-of-the-art algorithms that support the interpretability and explainability of machine learning models.

Machine Learning 110

Machine Learning Modeling 110

Data Science 101

SEPTEMBER 24, 2019

Is the list missing a project released in 2019? If so, please leave a comment.

Data Science 104

Data Science Deep Learning Machine Learning Visualization 104

Rocket-Powered Data Science

MARCH 19, 2021

One CIO said it this way , “If CIOs invested in machine learning three years ago, they would have wasted their money. This article quotes an older market projection (from 2019) , which estimated “the global industrial IoT market could reach $14.2 But if they wait another three years, they will never catch up.”

Internet of Things 259

Internet of Things Analytics IoT Prescriptive Analytics 259

CIO Business Intelligence

DECEMBER 17, 2024

When we started with generative AI and large language models, we leveraged what providers offered in the cloud. Now that we have a few AI use cases in production, were starting to dabble with in-house hosted, managed, small language models or domain-specific language models that dont need to sit in the cloud.

Digital Transformation 105

Digital Transformation Data Processing Optimization Machine Learning 105

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 111

Machine Learning Deep Learning Modeling Interactive 111

KDnuggets

AUGUST 1, 2019

A machine learning model that predicts some outcome provides value. Learn how Interpretable and Explainable ML technologies can help while developing your model. One that explains why it made the prediction creates even more value for your stakeholders.

Machine Learning 108

Machine Learning Modeling Technology IT 108

KDnuggets

SEPTEMBER 9, 2019

In this blog, Seth DeLand of MathWorks discusses two of the most common obstacles relate to choosing the right classification model and eliminating data overfitting.

Machine Learning 122

Machine Learning Modeling 122

CIO Business Intelligence

NOVEMBER 1, 2024

Paul Beswick, CIO of Marsh McLennan, served as a general strategy consultant for most of his 23 years at the firm but was tapped in 2019 to relaunch the risk, insurance, and consulting services powerhouse’s global digital practice. Gen AI is quite different because the models are pre-trained,” Beswick explains.

IT 122

IT Insurance Consulting Risk 122

Smart Data Collective

JUNE 24, 2023

Fortunately, new advances in machine learning technology can help mitigate many of these risks. Therefore, you will want to make sure that your cryptocurrency wallet or service is protected by machine learning technology. In 2018, researchers used data mining and machine learning to detect Ponzi schemes in Ethereum.

Machine Learning 98

Machine Learning Broadcasting Risk Data mining 98

Rocket-Powered Data Science

MARCH 10, 2020

In 2019, I was asked to write the Foreword for the book “ Graph Algorithms: Practical Examples in Apache Spark and Neo4j “ , by Mark Needham and Amy E. And this: perhaps the most powerful node in a graph model for real-world use cases might be “context”. How does one express “context” in a data model?

Metadata 250

Metadata Machine Learning Prescriptive Analytics ROI 250

datapine

NOVEMBER 27, 2019

2019 was a particularly major year for the business intelligence industry. While we work on programs to avoid such inconvenience , AI and machine learning are revolutionizing the way we interact with our analytics and data management while increment in security measures must be taken into account.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

DECEMBER 11, 2019

SaaS is a software distribution model that offers a lot of agility and cost-effectiveness for companies, which is why it’s such a reliable option for numerous business models and industries. 2019 was a breakthrough year for the SaaS world in many ways. Instead, they have the option of utilizing various pricing structures.

Software 314

Software Cost-Benefit Data-driven Data Processing 314

KDnuggets

OCTOBER 23, 2019

In this crash course on GANs, we explore where they fit into the pantheon of generative models, how they've changed over time, and what the future has in store for this area of machine learning.

Machine Learning 100

Machine Learning Modeling 100

KDnuggets

DECEMBER 10, 2019

This blog will explain the basics of deploying a machine learning algorithm, focusing on developing a Naïve Bayes model for spam message identification, and using Flask to create an API for that model.

Machine Learning 71

Machine Learning Modeling 71

O'Reilly on Data

NOVEMBER 18, 2019

In this interview from O’Reilly Foo Camp 2019, Hands-On Unsupervised Learning Using Python author Ankur Patel discusses the challenges and opportunities in making machine learning and AI accessible and financially viable for enterprise applications. Then you have pre-trained models you can do transfer learning with.

ROI 167

ROI Unstructured Data Machine Learning Modeling 167

KDnuggets

DECEMBER 16, 2019

Once you have deployed your machine learning model into production, differences in real-world data will result in model drift. This guide defines model drift and how to identify it, and includes approaches to enable model training. So, retraining and redeploying will likely be required.

Modeling 116

Modeling Machine Learning IT 116

CIO Business Intelligence

NOVEMBER 1, 2024

Paul Beswick, CIO of Marsh McLellan, served as a general strategy consultant for most of his 23 years at the firm but was tapped in 2019 to relaunch the risk, insurance, and consulting services powerhouse’s global digital practice. Gen AI is quite different because the models are pre-trained,” Beswick explains.

IT 105

IT Insurance Consulting Risk 105

KDnuggets

SEPTEMBER 19, 2019

While mature algorithms and extensive open-source libraries are widely available for machine learning practitioners, sufficient data to apply these techniques remains a core challenge. Discover how to leverage scikit-learn and other tools to generate synthetic data appropriate for optimizing and fine-tuning your models.

Machine Learning 99

Machine Learning Optimization Modeling 99

datapine

NOVEMBER 19, 2019

While we’ve seen traces of this in 2019, it’s in 2020 that computer vision will make a significant mark in both the consumer and business world. Already in our shortlist of tech buzzwords 2019, artificial intelligence is on the front scene for next year again. Artificial Intelligence (AI). Connected Retail. Hyperautomation.

Technology 279

Technology Internet of Things IT IoT 279

erwin

DECEMBER 13, 2018

We’re making the following data governance predictions for 2019: Top 10 Data Governance Predictions for 2019. GDPR fines are coming and they will be massive : Perhaps one of the safest data governance predictions for 2019 is the coming clamp down on GDPR enforcement. Data is no longer just an IT issue.

Data Governance 91

Data Governance IoT Internet of Things Data-driven 91