DataRobot

OCTOBER 18, 2021

I have a confession to make—I’m a back-seat driver! When sitting in a taxi, I can’t help but grumble when the ride isn’t smooth, or the driver chooses the slowest lane of traffic. I have to fight the urge to take control. When it comes to shopping, I passively accept what is offered for sale. But my wife, who grew up in Asia where haggling is part of the culture, is different.

Forecasting 145

Forecasting Digital Transformation Cost-Benefit Data-driven 145

Analytics Vidhya

OCTOBER 18, 2021

This article was published as a part of the Data Science Blogathon Learn how machine learning pipelines are used in productions and design your first pipeline using simple steps on disaster tweets classification datasets. You will also learn how to ingest the data, preprocess, train, and eventually evaluate the results. Image 1 Introduction In this […].

Machine Learning 328

Machine Learning Data Science Publishing Analytics 328

DataKitchen

OCTOBER 18, 2021

The post 5 hot new IT jobs — and why they just might stick first appeared on DataKitchen.

IT 356

IT 356

Analytics Vidhya

OCTOBER 18, 2021

This article was published as a part of the Data Science Blogathon Overview of Text Analysis in Julia The article majorly focuses on how to make you comfortable with the outline of Julia text processing tools with a brief explanation of their use in projects. Here we see the TextAnalysis package of Julia with the functionalities […]. The post Text Analysis in Natural Language Processing using Julia appeared first on Analytics Vidhya.

Data Science 278

Data Science Publishing Analytics 278

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Cloudera

OCTOBER 18, 2021

It’s that time of year again… Award season! We are thrilled to announce the finalists of the 2021 Data Impact Awards. This year’s entrants have excelled at demonstrating how innovative data solutions can help solve real-time challenges and positively impact people around the world. . The entries are some of the most remarkable we’ve seen, giving our judges the tough task of selecting an award worthy shortlist.

Enterprise 106

Enterprise Finance Consulting Management 106

Dataiku

OCTOBER 18, 2021

On a recent webinar with Jim Kobelius of TDWI (that you can watch below), we talked about mature MLOps. You can watch our presentations, but I thought it would be helpful to summarize some of the concepts based on over ten years working with machine learning and, over the last three and a half years, specifically focusing on MLOps.

Machine Learning 105

Machine Learning IT 105

Octopai

OCTOBER 18, 2021

First, what active metadata management isn’t : “Okay, you metadata! Quit lounging around! We’re gonna move those bits and bytes! Everyone, get into position and… one – and zero! And one – and zero!”. Now, what active metadata management is (well, kind of): “Okay, you metadata! Quit lounging around! You’re going to start pulling your weight here and deliver actionable insights that we can use to improve our business immediately!”.

Metadata 83

Metadata Management IT Data Quality 83

Teradata

OCTOBER 18, 2021

Risk management in banks is undergoing a rapid transformation, accelerated by COVID, but with causes and potential impacts that go deeper. Find out more.

Risk 52

Risk Risk Management Management 52

The Data Visualisation Catalogue

OCTOBER 18, 2021

For ages, the naming between Sankey Diagrams , Parallel Sets , and Alluvial Diagrams have been used interchangeably. Are these visualisations that different from one another and is it a bad thing that some misnaming is taking place? From my research into the various visualisation types, it’s common to see a particular visualisation type being identified under multiple names.

Visualization 94

Visualization IT 94

Domino Data Lab

OCTOBER 18, 2021

The opportunities to solve problems with the use of data are greater than ever, and as different industries embrace them, the available data has been steadily increasing and the number of tools expanded. A typical question that new data scientists ask is related to the best programming language to learn, either to get a good understanding of coding or to future-proof their skills.

Data Science 52

Data Science Machine Learning 52

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

Jet Global

OCTOBER 18, 2021

For years, business leaders have struggled with the challenges of getting the right product to the right place at the right time. When a company ends up with too much inventory on hand, its capital is tied up in goods stored in the warehouse, so it can’t be put to use elsewhere. Instead of paying down debt, saving on interest expense, and preserving liquidity; its cash is committed to maintaining bloated levels of inventory.

Forecasting 52

Forecasting Recreation/Entertainment Sales Finance 52