Analytics Vidhya

DECEMBER 29, 2021

This article was published as a part of the Data Science Blogathon Overview This Pokemon will analyze the pokemon dataset and predict whether the Pokemon is legendary based on the features provided. We will discuss everything from scratch; we will go from CSV to model building with line by line explanation of code. Let’s get started. Image […].

Data Science 400

Data Science Publishing Modeling Analytics 400

KDnuggets

DECEMBER 29, 2021

AI/ML systems have a wide range of applications in a variety of industries and sectors, and this article highlights the top ways AI/ML will impact your small business in 2022.

Technology 156

Technology Machine Learning 156

Analytics Vidhya

DECEMBER 29, 2021

This article was published as a part of the Data Science Blogathon Welcome to my guide! In this guide, we will cover basic as well as advanced topics involved in Deep Learning. This guide will help you in gaining confidence in the concepts of Deep Learning. So let’s begin with our journey! Why do we need […]. The post A Guide on Deep Learning: From Basics to Advanced Concepts appeared first on Analytics Vidhya.

Deep Learning 393

Deep Learning Data Science Publishing Analytics 393

KDnuggets

DECEMBER 29, 2021

It's time to learn: machine learning is not a Swiss Army knife.

Machine Learning 160

Machine Learning IT 160

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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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Dataiku

DECEMBER 29, 2021

Many organizations believe that they need to have all their data ducks lined up before they attempt AI analytics. They believe they need to have conquered traditional or business intelligence (BI) analytics first, including data catalogs, data lineage, master data management, big data, etc. before planning for AI. While this conventional thinking has merits, it results in high opportunity costs and carries risks.

Business Intelligence 69

Business Intelligence Big Data Risk Management 69

Smart Data Collective

DECEMBER 29, 2021

Big data has become a very important part of modern business. Companies are using big data technology to improve their human resources, financial management and marketing strategies. Digital marketing , in particular, is very dependent on big data. Companies are expected to spend over $5 billion on big data marketing services in 2026. One of the most important big data applications in marketing is with SEO.

Big Data 131

Big Data Marketing Data mining Data-driven 131

The Data Visualisation Catalogue

DECEMBER 29, 2021

Many of us in the western data visualisation community may think of data visualisation as a field that primarily emerged out of the West. If you were to name key historical practitioners of data visualisation, likely, the names Charles Joseph Minard , Florence Nightingale , William Playfair or Charles Dupin come to mind. But you’re unlikely to know that the Japanese have been using charts since the 1800s to aid in market trading.

Publishing 136

Publishing Visualization Marketing Statistics 136