Dataiku

MARCH 7, 2022

Bad news: migrating to the cloud isn’t a data architecture strategy, and it most likely (in and of itself) won’t solve the biggest points of friction, challenges, or problems your team is currently facing. Here’s why.

Strategy 59

Strategy Data Architecture IT 59

Analytics Vidhya

MARCH 7, 2022

This article was published as a part of the Data Science Blogathon. Image source: Author Introduction Visualization plays an important role in the decision-making process after analyzing relevant data. Graphical representation highlighting the interdependence of key elements affecting performance is important in the above process.

Visualization 284

Visualization Data Science Publishing Analytics 284

KDnuggets

MARCH 7, 2022

In this article, you will learn to export your models and use them outside a Jupyter Notebook environment. You will build a simple web application that is able to feed user input into a machine learning model, and display an output prediction to the user.

Machine Learning 127

Machine Learning Modeling 127

Analytics Vidhya

MARCH 7, 2022

This article was published as a part of the Data Science Blogathon. Source: Unsplash.com There are many data science fields, you will have to work closely with your business to identify issues. You will get many articles telling tips for creating a solid profile, but no one will tell you which profile you should pick as […]. The post What were you thinking when you choose your Data Scientist Profile?

Data Science 270

Data Science Publishing Analytics 270

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Visualization

KDnuggets

MARCH 7, 2022

Learn these to take any data science project idea from brainstorm to deployment.

Data Science 158

Data Science 158

Analytics Vidhya

MARCH 7, 2022

This article was published as a part of the Data Science Blogathon. A Feed Forward Neural Network is an artificial Neural Network in which the nodes are connected circularly. A feed-forward neural network, in which some routes are cycled, is the polar opposite of a Recurrent Neural Network. The feed-forward model is the basic type of […]. The post Basic Introduction to Feed-Forward Network in Deep Learning appeared first on Analytics Vidhya.

Deep Learning 270

Deep Learning Data Science Publishing Modeling 270

Analytics Vidhya

MARCH 7, 2022

This article was published as a part of the Data Science Blogathon. One of the important use cases of Natural Language Processing (NLP) is generative text. Generative text is predicting what word must come next in a sentence. Applications of generative text are question-answering chatbots, sentence or word autocorrection, and autocompletion, grammar check, and these cases […].

Data Science 270

Data Science Publishing Analytics 270

Nutanix

MARCH 7, 2022

A reimagined Security Planning now delivers Flow microsegmentation policy auto-generation, complete network view & intelligent VM category management

Management 44

Management 44

Analytics Vidhya

MARCH 7, 2022

Dear Readers, We are excited to announce a new webinar adding to ‘The DataHour’ We are delighted to share that we are bringing one of the top industry leaders’ Laurent Picard’ to help us to enable deeper discussions and conversations with our cherished community. Date: 15th March Time: 7:30pm to 8:30pm IST Topic: Building Smarter […].

Analytics 269

Analytics 269

Occam's Razor

MARCH 7, 2022

If there is one thing the universe agrees on, it is that you should just provide data… You should provide INSIGHTS!!! In the 807,150 (!) words I’ve written on this blog thus far, at least 400,000 have been dedicated to helping you find insights. In posts about advanced segmentation , in posts about how to build strategic dashboards that don’t suck , in encouraging you to reimagine how you pick metrics to obsess about using the magnificent Impact Matrix , and on and on and on.

Key Performance Indicator 101

Key Performance Indicator Strategy Marketing Publishing 101

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.

Management