CIO Business Intelligence

NOVEMBER 22, 2022

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. As with just about everything in IT, a data strategy must evolve over time to keep pace with evolving technologies, customers, markets, business needs and practices, regulations, and a virtually endless number of other priorities.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

Analytics Vidhya

NOVEMBER 14, 2022

This article was published as a part of the Data Science Blogathon. Introduction Flutter where F stands for Front- end, L stands for Language, U stands for UI layout, T stands for Time, T stands for Tools, E stands for Enable, and R stands for Rich. In other words, Flutter is a tool used in […]. The post Building Our Applications Using Flutter appeared first on Analytics Vidhya.

Data Science 394

Data Science Publishing Analytics 394

O'Reilly on Data

JUNE 7, 2022

DeepMind’s new model, Gato, has sparked a debate on whether artificial general intelligence (AGI) is nearer–almost at hand–just a matter of scale. Gato is a model that can solve multiple unrelated problems: it can play a large number of different games, label images, chat, operate a robot, and more. Not so many years ago, one problem with AI was that AI systems were only good at one thing.

Modeling 363

Modeling Interactive Optimization Deep Learning 363

KDnuggets

DECEMBER 19, 2022

RPA and IA have stunned the business world by availing impressive, intelligent automation capabilities for scales of businesses across industries, which we'll know in this blog.

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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence

DataRobot Blog

DECEMBER 6, 2022

Savvy data scientists are already applying artificial intelligence and machine learning to accelerate the scope and scale of data-driven decisions in strategic organizations. These data science teams are seeing tremendous results—millions of dollars saved, new customers acquired, and new innovations that create a competitive advantage. Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results.

Experimentation 145

Experimentation Forecasting Data-driven Machine Learning 145

TDAN

FEBRUARY 16, 2022

No, this is not a mistyping of data literacy. Yes, like everyone, I am aware of and fully on-board with the growing movement to improve data literacy in the enterprise. What I want to talk about is Data Littering, which is something else entirely. Data Littering is the deliberate act of creating and distributing data […].

Enterprise 145

Enterprise Data Quality Data Governance Metadata 145

Timo Elliott

JANUARY 3, 2022

Back in the 1960s, a pair of radio astronomers were busily collecting data on distant galaxies. They had been doing this for years. Elsewhere, other astronomers had been doing the same. But what set these astronomers apart – and eventually earned them a Nobel Prize – was what they eventually found in the data. Like other radio astronomers, they had long detected a consistent noise pattern.

IT 143

IT Unstructured Data Data Quality Machine Learning 143

Jen Stirrup

NOVEMBER 15, 2022

Information is pretty thin stuff, unless mixed with experience. – Clarence Day (1874–1935), American essayist. Why do organizations get stuck with their data? It is such a fundamental question. Often, this problem can be due to the organization concentrating solely on technology and data. However, organizations can be supported by a synergistic approach by integrating systems thinking with the data strategy and technical perspective.

Data Science 145

Data Science Digital Transformation Data-driven Measurement 145

DataRobot

JANUARY 20, 2022

Shifting to Proactive Healthcare Delivery with AI. The Case for Change. The UK Government Health and Care Bill sets up Integrated Care Systems (ICSs) as legal entities from July 2022. While ICSs have been operating in shadow-format for a number of years, this long-awaited shift determines that health and care delivery in England is regionally managed and focused around the needs of the local population.

Data-driven 145

Data-driven Experimentation Predictive Modeling Modeling 145

Analytics Vidhya

APRIL 14, 2022

This article was published as a part of the Data Science Blogathon. Source: Forbes.com Introduction It is not hidden from the audience that quantum computing is the future of data processing. Tech giants like IBM, Google, and Microsoft are all aggressively pursuing quantum computing technology for a good reason. The massive speedups and power savings of quantum […].

Data Science 400

Data Science Publishing Data Processing Technology 400

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Data-driven

Analytics Vidhya

OCTOBER 16, 2022

This article was published as a part of the Data Science Blogathon. Introduction Niti Ayog, one of the transforming national institutions, has published an article on Blockchain use cases in India. Few questions about Blockchain, why Blockchain, and how we can deploy our applications through the docker and Kubernetes we should know. Objectives We will discuss […].

Publishing 395

Publishing Data Science Analytics 395

Analytics Vidhya

OCTOBER 7, 2022

This article was published as a part of the Data Science Blogathon. Introduction With the increasing use of technology, data accumulation is faster than ever due to connected smart devices. These devices continuously collect and transmit data that can be processed, transformed, and stored for later use. This collected data, known as big data, holds valuable […].

Big Data 399

Big Data Data Science Publishing Technology 399

Analytics Vidhya

AUGUST 4, 2022

This article was published as a part of the Data Science Blogathon. Introduction Requests in Python is a module that can be used to send all kinds of HTTP requests. It is straightforward to use and is a human-friendly HTTP Library. Using the requests library; we do not need to manually add the query string […]. The post Introduction to Requests Library in Python appeared first on Analytics Vidhya.

Data Science 399

Data Science Publishing Analytics IT 399

Analytics Vidhya

SEPTEMBER 11, 2022

This article was published as a part of the Data Science Blogathon. Introduction Blockchain technology is a decentralized, distributed ledger that keeps a record of ownership of digital assets. Any data stored on the blockchain cannot be modified, making the technology a legitimate disruptor for payments, cybersecurity, and healthcare industries. Blockchain is a system of registering […].

Technology 397

Technology IT Data Science Publishing 397

Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

Marketing

Analytics Vidhya

MARCH 17, 2022

This article was published as a part of the Data Science Blogathon. Photo by Kanchanara on Unsplash Table of Contents Introduction Gentle Overview What is Time Series Analysis? Types of analysis ARIMA Moving Average Exponential Smoothing Heard of DogeCoin? Implementation of Dogecoin price prediction Conclusion Introduction Machine learning will automate jobs that most people thought could […].

Machine Learning 399

Machine Learning Data Science Publishing Analytics 399

Analytics Vidhya

JULY 31, 2022

This article was published as a part of the Data Science Blogathon. Introduction to EDA The main objective of this article is to cover the steps involved in Data pre-processing, Feature Engineering, and different stages of Exploratory Data Analysis, which is an essential step in any research analysis. Data pre-processing, Feature Engineering, and EDA are fundamental early […].

Data Science 391

Data Science Publishing Analytics Visualization 391

KDnuggets

AUGUST 24, 2022

This blog post introduces seven techniques that are commonly applied in domains like intrusion detection or real-time bidding, because the datasets are often extremely imbalanced.

Machine Learning 160

Machine Learning 160

KDnuggets

MAY 26, 2022

Read the best books on Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, MLOps, Robotics, IoT, AI Products Management, and Data Science for Executives.

Data Science 160

Data Science Deep Learning IoT Machine Learning 160

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

Business Intelligence

KDnuggets

DECEMBER 30, 2022

Data science is ever-evolving, so mastering its foundational technical and soft skills will help you be successful in a career as a Data Scientist, as well as pursue advance concepts, such as deep learning and artificial intelligence.

Data Science 160

Data Science Deep Learning IT 160

KDnuggets

DECEMBER 30, 2022

It's time again to look at some data science cheatsheets. Here you can find a short selection of such resources which can cater to different existing levels of knowledge and breadth of topics of interest.

Data Science 160

Data Science IT 160

KDnuggets

DECEMBER 16, 2022

Many aspiring Data Scientists, especially when self-learning, fail to learn the necessary math foundations. These recommendations for learning approaches along with references to valuable resources can help you overcome a personal sense of not being "the math type" or belief that you "always failed in math.".

Data Science 160

Data Science 160

KDnuggets

DECEMBER 9, 2022

As more people are entering the field of Data Science and more companies are hiring for data-centric roles, what type of jobs are currently in highest demand? There is so much data in the world, and it just keeps flooding in, it now looks like companies are targeting those who can engineer that data more than those who can only model the data.

Data Science 160

Data Science Modeling IT 160

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.

Data-driven

KDnuggets

DECEMBER 1, 2022

In this blog, I shared my story on getting 4 data science job offers including Airbnb, Lyft and Twitter after being laid off. Any data scientist who was laid off due to the pandemic or who is actively looking for a data science position can find something here to which they can relate.

Data Science 160

Data Science 160

KDnuggets

SEPTEMBER 1, 2022

Subset selection is one of the most frequently performed tasks while manipulating data. Pandas provides different ways to efficiently select subsets of data from your DataFrame.

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KDnuggets

NOVEMBER 23, 2022

There exist so many great computational tools available for Data Scientists to perform their work. However, mathematical skills are still essential in data science and machine learning because these tools will only be black-boxes for which you will not be able to ask core analytical questions without a theoretical foundation.

Data Science 160

Data Science Machine Learning Analytics 160

KDnuggets

NOVEMBER 18, 2022

The Pandas library is core to any Data Science work in Python. This introduction will walk you through the basics of data manipulating, and features many of Pandas important features.

Data Science 160

Data Science 160

Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage

Christophe Louvion, Chief Product & Technology Officer of NRC Health, is here to take us through how he guided his company's recent experience of getting from concept to launch and sales of products within 90 days. In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.

Sales

KDnuggets

NOVEMBER 16, 2022

While different ways to learn Data Science for the first time exist, the approach that works for you should be based on how you learn best. One powerful method is to evolve your learning from simple practice into complex foundations, as outlined in this learning path recommended by a physicist who turned into a Data Scientist.

Data Science 160

Data Science IT 160

KDnuggets

FEBRUARY 14, 2022

Calculus is the key to fully understanding how neural networks function. Go beyond a surface understanding of this mathematics discipline with these free course materials from MIT.

Deep Learning 160

Deep Learning Machine Learning 160

KDnuggets

OCTOBER 19, 2022

This post is a summary of 2 distinct frameworks for approaching machine learning tasks, followed by a distilled third. Do they differ considerably (or at all) from each other, or from other such processes available?

Machine Learning 160

Machine Learning 160

KDnuggets

OCTOBER 24, 2022

Preprocessing data for machine learning models is a core general skill for any Data Scientist or Machine Learning Engineer. Follow this guide using Pandas and Scikit-learn to improve your techniques and make sure your data leads to the best possible outcome.

Machine Learning 160

Machine Learning Modeling 160

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Adding high-quality entity resolution capabilities to enterprise applications, services, data fabrics or data pipelines can be daunting and expensive. Organizations often invest millions of dollars and years of effort to achieve subpar results. This guide will walk you through the requirements and challenges of implementing entity resolution. By the end, you'll understand what to look for, the most common mistakes and pitfalls to avoid, and your options.

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