Analytics Vidhya

SEPTEMBER 8, 2021

This article was published as a part of the Data Science Blogathon Introduction We all know the phrase: “Every picture can tell us a story” There could be a lot of information hidden inside an image and we could interpret it in different ways and perspectives. So, what is an image, and how to deal with […]. The post A Beginner’s Guide to Image Processing With OpenCV and Python appeared first on Analytics Vidhya.

Data Science 400

Data Science Publishing Analytics IT 400

DataKitchen

SEPTEMBER 8, 2021

The post Big Data 50: Companies Driving Innovation first appeared on DataKitchen.

Big Data 223

Big Data 223

Analytics Vidhya

SEPTEMBER 8, 2021

This article was published as a part of the Data Science Blogathon Introduction to Geometric Intuition of Logistic Regression Hello folks! You may generally come across the term classification and regression in our data science or machine learning community, this two are the main pillars of machine learning. classification is all about predicting the label and regression […].

Machine Learning 315

Machine Learning Data Science Publishing Analytics 315

Smart Data Collective

SEPTEMBER 8, 2021

More and more businesses and organizations treat data as an essential asset. The importance of managing and leveraging data cannot be overestimated. The process of interpreting and analyzing data and putting it into context helps businesses and organizations make informed decisions, predict trends, anticipate expectations, improve security, optimize internal operations, and stay ahead of competitors.

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Data-driven Data Analytics Analytics Marketing 127

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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.

Analytics Vidhya

SEPTEMBER 8, 2021

This article was published as a part of the Data Science Blogathon Introduction There are many tutorials and video lectures on the Web, and other materials discussing the basic principles of building neural networks, their architecture, learning strategies, etc. Traditionally, neural networks are trained by presenting image packets from the training sample to the neural network […].

Data Science 297

Data Science Publishing Strategy Analytics 297

Dataiku

SEPTEMBER 8, 2021

This article presents how financial modeling can be done inside Dataiku. Let’s begin with the context: spreadsheet-based tools like Microsoft Excel are some of the most popular tools for financial modeling and are used for all kinds of tasks including investment analysis, P&L modeling, and risk management. Why is that the case? Spreadsheets have convenience benefits, they have been around for a long time, and they will continue to be around for the foreseeable future.

Modeling 105

Modeling Risk Management Risk Management 105

Smart Data Collective

SEPTEMBER 8, 2021

Machine learning has made app development much easier than ever, even for people without previous coding experience. Once upon a time, coding and developing seemed like it was something hard and far-fetched for anyone with no previous experience. Only those who studied software building, coding, and development could do this, but this isn’t the case anymore.

Machine Learning 96

Machine Learning Software Testing IT 96

Analytics Vidhya

SEPTEMBER 8, 2021

This article was published as a part of the Data Science Blogathon Introduction We are living in an era of data. Every day we generate thousands of terabytes of data. This data can be the sales records of a company, the activity of users on an application, your payment history, etc. Using this data, we are creating […]. The post Using The Right File Format For Storing Data appeared first on Analytics Vidhya.

Sales 291

Sales Data Science Publishing Analytics 291

Paul Blogs on BI

SEPTEMBER 8, 2021

While we have definitely seen an acceleration in organizations using or moving operational applications to the cloud, Business Intelligence has lagged behind. Today, the majority of BusinessObjects customers use the product on premise and that will not change for a while. Why? Well firstly, if the main data warehouses, repositories, or application databases that BusinessObjects accesses are on premise, it makes no sense to move BusinessObjects to the cloud until you move its data sources to the

Data Warehouse 59

Data Warehouse Data Processing Data Lake Testing 59

Analytics Vidhya

SEPTEMBER 8, 2021

This article was published as a part of the Data Science Blogathon The speed of Deep learning and neural networks is increasingly indispensable for thousands of industries. One of the main problems they face is deploying complex kinds of applications. I want to show you a practical and convenient way of such a deployment, for which […]. The post Serverless Tensorflow on AWS Lambda – A Tutorial For beginners appeared first on Analytics Vidhya.

Deep Learning 278

Deep Learning Data Science Publishing Analytics 278

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.

Nutanix

SEPTEMBER 8, 2021

There is some wisdom in compromise—in striking a balance between two equally important, albeit opposing, halves. And while that philosophy may ring true in everything from relationships to purchasing a new home, enterprises nowadays aren’t looking to just balance when it comes to their cloud architecture.

Enterprise 46

Enterprise IT 46

Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements. ETL is one of the most integral processes required by Business Intelligence and Analytics use cases since it relies on the data stored in Data Warehouses to build reports and visualizations

Data Warehouse 91

Data Warehouse Data Integration Marketing Software 91

Sisense

SEPTEMBER 8, 2021

Blog. The steady growth of medical data is outpacing many health providers’ ability to make use of it. Data mining and analytics tools previously used for commercial data are being applied to medical data in various forms. In 2020, for instance, experts from Sisense joined forces with the G-Med online community to create the Medin’Sight app to help fight COVID-19, and Sisense client GeriMedica began infusing analytics insights into practitioner workflows to improve elder care.

Analytics 52

Analytics Data mining Data Integration Risk 52

Cloudera

SEPTEMBER 8, 2021

In recent years there has been increased interest in how to safely and efficiently extend enterprise data platforms and workloads into the cloud. CDOs are under increasing pressure to reduce costs by moving data and workloads to the cloud, similar to what has happened with business applications during the last decade. Our upcoming webinar is centered on how an integrated data platform supports the data strategy and goals of becoming a data-driven company.

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Data Lake Enterprise Data-driven Data Strategy 75

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Experimentation