Smart Data Collective

SEPTEMBER 30, 2021

But what if machine learning could be used beyond niche or individual contexts? Below, we’ll be exploring a few of the ways that machine learning can be used for improving our cities and making them smarter overall. There is growing evidence big data and machine learning can help save the environment.

Machine Learning 119

Machine Learning Cost-Benefit Optimization Forecasting 119

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 75

Machine Learning Modeling 75

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

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 110

Machine Learning Modeling 110

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 98

Insurance Machine Learning Cost-Benefit Risk 98

O'Reilly on Data

OCTOBER 31, 2019

Theodore Summe offers a glimpse into how Twitter employs machine learning throughout its product. Watch “ Personalization of Spotify Home and TensorFlow “ TensorFlow Hub: The platform to share and discover pretrained models for TensorFlow. Watch “ Opening keynote “ Accelerating ML at Twitter.

IoT 190

IoT Machine Learning Modeling Software 190

O'Reilly on Data

MARCH 19, 2020

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. Unsupervised learning is growing. Growth in ML and AI is unabated.

Deep Learning 276

Deep Learning Machine Learning Data-driven Modeling 276

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 92

Machine Learning Sales Data-driven Big Data 92

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

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 120

Machine Learning Modeling 120

KDnuggets

NOVEMBER 6, 2019

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

Machine Learning 85

Machine Learning Modeling 85

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 53

Machine Learning Modeling 53

IBM Big Data Hub

APRIL 13, 2023

After developing a machine learning model, you need a place to run your model and serve predictions. If your company is in the early stage of its AI journey or has budget constraints, you may struggle to find a deployment system for your model. Db2 Warehouse on cloud also supports these ML features.

Modeling 91

Modeling Statistics Machine Learning Testing 91

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 91

Machine Learning Modeling 91

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

KDnuggets

SEPTEMBER 13, 2019

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

Machine Learning 98

Machine Learning Data Science Modeling 98

KDnuggets

OCTOBER 11, 2019

In this upcoming webinar on Oct 23 @ 10 AM PT, learn why you should invest time in monitoring your machine learning models, the dangers of not paying attention to how a model’s performance can change over time, metrics you should be gathering for each model and what they tell you, and much more.

Machine Learning 57

Machine Learning Metrics Modeling 57

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 87

Machine Learning Modeling Technology IT 87

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 88

Machine Learning Modeling 88

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 109

Modeling Machine Learning IT 109

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 104

Machine Learning Modeling 104

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 87

Machine Learning Optimization Modeling 87

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 332

Management Machine Learning Experimentation Metrics 332

Dataiku

FEBRUARY 19, 2020

In late 2019, Dataiku enlisted Gerson Lehrman Group (GLG) to administer an anonymous survey to 200 IT professionals across a range of industries. The goal of this survey was to uncover trends in data architecture in the enterprise, specifically in the context of operationalizing machine learning models.

Data Architecture 59

Data Architecture Enterprise Modeling Machine Learning 59

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 221

Machine Learning Modeling Technology IT 221

KDnuggets

OCTOBER 29, 2019

Developing an excellent machine learning model is one thing. Consider these lessons learned and recommendations for approaching this important challenge to help ensure value from your AI work. Deploying it to production is another.

Machine Learning 53

Machine Learning Modeling IT 53

Data Science 101

NOVEMBER 7, 2019

R Support for Azure Machine Learning. Azure Machine Learning now has a new web interface and it just got support for the R programming language. Azure Machine Learning is an environment to help with all the aspects of data science from data cleaning to model training to deployment.

Data Science 106

Data Science Machine Learning Data Lake IoT 106

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

KDnuggets

JULY 29, 2019

Recently, AI researchers from Microsoft open sourced the Decentralized & Collaborative AI on Blockchain project that enables the implementation of decentralized machine learning models based on blockchain technologies.

Machine Learning 51

Machine Learning Modeling Technology 51

KDnuggets

NOVEMBER 20, 2019

The two main takeaways from this paper: firstly, a sharpening of my understanding of the difference between explainability and interpretability, and why the former may be problematic; and secondly some great pointers to techniques for creating truly interpretable models.

Modeling 58

Modeling Machine Learning 58

Cloudera

MARCH 13, 2019

ING – Utilizing HDP and HDF for machine learning models to make relevant engagements with customers. Stay tuned for March 19, 2019 as the winners are unveiled at the Luminaries dinner in Barcelona. The post Introducing the 2019 Data Heroes – EMEA! appeared first on Cloudera Blog.

Data Architecture 69

Data Architecture Deep Learning Machine Learning Big Data 69

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 183

Machine Learning Data Collection Modeling IT 183

Smart Data Collective

SEPTEMBER 30, 2019

Machine learning and other big data technology has rendered password security a greater concern. Alexander Polyakov of Towards Data Science discussed some of the ways that they are using machine learning to exploit their victims. How effective is machine learning for breaking passwords?

Machine Learning 71

Machine Learning Big Data Risk Interactive 71

KDnuggets

SEPTEMBER 20, 2019

When we create our machine learning models, a common task that falls on us is how to tune them. So that brings us to the quintessential question: Can we automate this process?

Modeling 83

Modeling Machine Learning 83

DataRobot

JUNE 17, 2021

At the time, I had a small following of people interested in using Eureqa to derive mathematical formulas and models. This search for mathematical formulas makes Eureqa different from other machine learning algorithms. What Makes Eureqa Models Different from other Models. They also deploy very easily.

Modeling 52

Modeling Experimentation Machine Learning Measurement 52

CIO Business Intelligence

FEBRUARY 6, 2023

In the last few years, the [insurance industry] has taken us in some new directions, being more remote and virtual and changing behaviors than we would have seen in 2019 or before,” Harris-Ferrante says. So we had to kind of rethink and reimagine our whole model of engaging with policyholders or potential policyholders.”

Insurance 128

Insurance IT Digital Transformation Machine Learning 128

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 132

ROI Unstructured Data Machine Learning Modeling 132