Sisense

APRIL 10, 2020

We’ll actually do this later in this article. These support a wide array of uses, such as data analysis, manipulation, visualizations, and machine learning (ML) modeling. Some standard Python libraries are Pandas, Numpy, Scikit-Learn, SciPy, and Matplotlib. R libraries. Modeling in R and Python.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Smart Data Collective

APRIL 25, 2022

Throughout this article it will be discussed in more detail how different departments in your company can benefit from using artificial intelligence to manage their online profile. Instead, machine learning algorithms can be much more effective when tracking online reviews. This is key when it comes to attracting new customers.

Management 135

Management Machine Learning Marketing Deep Learning 135

Smart Data Collective

MAY 8, 2022

Brands are closely working to solve this as they dive deep into the world of big data analytics. Well, don’t go anywhere because, in this article, we will show you how you can use big data analytics combined with AI to achieve the best performance possible. What is the relationship between big data analytics and AI?

Big Data 106

Big Data Data Analytics Analytics Cost-Benefit 106

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Rocket-Powered Data Science

JULY 6, 2021

I provide below my perspective on what was interesting, innovative, and influential in my watch list of the Top 10 data innovation trends during 2020. 1) Automated Narrative Text Generation tools became incredibly good in 2020, being able to create scary good “deep fake” articles.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Introduction.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

Insight

JANUARY 14, 2020

In short, I was faced with two major difficulties regarding data collection: I didn’t have nearly enough images, and the images I did have were not representative of a realistic gym environment. Check out this great Medium article that discusses the difference between tensors and multidimensional arrays.

Metrics 58

Metrics Optimization Modeling Testing 58

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

OCTOBER 9, 2019

Paco Nathan’s latest article covers data practices from the National Oceanic and Atmospheric Administration (NOAA) Environment Data Management (EDM) workshop as well as updates from the AI Conference. The data must be converted into a variety of supported formats for download, including JSON-LD. Introduction.

Deep Learning 69

Deep Learning Metadata Machine Learning Data Science 69

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Occam's Razor

OCTOBER 12, 2017

I read articles they write. Intro to Machine Learning. Machine Learning. Deep Learning. For Digital Analysts, it is creating data collection mechanisms, writing queries, creating reports, doing segmentation, creating rules, identifying business focus areas based on data etc.

Marketing 136

Marketing Analytics Machine Learning Strategy 136