Sat.Dec 28, 2019 - Fri.Jan 03, 2020

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Predict Electricity Consumption Using Time Series Analysis

KDnuggets

Time series forecasting is a technique for the prediction of events through a sequence of time. In this post, we will be taking a small forecasting problem and try to solve it till the end learning time series forecasting alongside.

IT 135
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Building The DataDog Platform For Processing Timeseries Data At Massive Scale

Data Engineering Podcast

Summary DataDog is one of the most successful companies in the space of metrics and monitoring for servers and cloud infrastructure. In order to support their customers, they need to capture, process, and analyze massive amounts of timeseries data with a high degree of uptime and reliability. Vadim Semenov works on their data engineering team and joins the podcast in this episode to discuss the challenges that he works through, the systems that DataDog has built to power their business, and how

Process 100
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Don’t Organize for AI, Organize for Analytics

Teradata

How do you organize your business for analytics? Here are six steps your enterprise should take when creating an analytics team. Read more!

59
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Celebrating 1,000 Employees and Looking Towards the Path Ahead

Confluent

During the holiday season, it’s a particularly relevant time to pause, reflect, and celebrate, both the days past and those ahead. Here at Confluent, it’s a noticeably nostalgic moment, given […].

19
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15 Modern Use Cases for Enterprise Business Intelligence

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?

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What is the most important question for Data Science (and Digital Transformation)

KDnuggets

With so many buzzwords surrounding AI and machine learning, understanding which can bring business value and which are best left in the lab to mature is difficult. While machine learning offers significant power in driving digital transformations, a business must start with the right questions and leave the math to the development teams.

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Why Python is One of the Most Preferred Languages for Data Science?

KDnuggets

Why do most data scientists love Python? Learn more about how so many well-developed Python packages can help you accomplish your crucial data science tasks.

More Trending

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How To “Ultralearn” Data Science: summary, for those in a hurry

KDnuggets

For those of you in a hurry and interested in ultralearning (which should be all of you), this recap reviews the approach and summarizes its key elements -- focus, optimization, and deep understanding with experimentation -- geared toward learning Data Science.

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Beginner’s Guide to K-Nearest Neighbors in R: from Zero to Hero

KDnuggets

This post presents a pipeline of building a KNN model in R with various measurement metrics.

Building 126
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Accuracy vs Speed – what Data Scientists can learn from Search

KDnuggets

Delivering accurate insights is the core function of any data scientist. Navigating the development road toward this goal can sometimes be tricky, especially when cross-collaboration is required, and these lessons learned from building a search application will help you negotiate the demands between accuracy and speed.

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Top KDnuggets tweets, Dec 18-30: A Gentle Introduction to Math Behind Neural Networks

KDnuggets

A Gentle Introduction to #Math Behind #NeuralNetworks; Learn How to Quickly Create UIs in Python; I wanna be a data scientist, but. how!?; I created my own deepfake in two weeks.

Python 63
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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

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.

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Towards a Quantitative Measure of Intelligence: Breaking Down One of the Most Important AI Papers of 2019, Part II

KDnuggets

AI scientist Francois Chollet proposes a better framework for measuring the intelligence of AI systems.

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Towards a Quantitative Measure of Intelligence: Breaking Down One of the Most Important AI Papers of 2019, Part I

KDnuggets

AI scientist Francois Chollet proposes a better framework for measuring the intelligence of AI systems.

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Don’t Organize for AI, Organize for Analytics

Teradata

How do you organize your business for analytics? Here are six steps your enterprise should take when creating an analytics team. Read more!

58
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How HR Is Using Data Science and Analytics to Close the Gender Gap

KDnuggets

The gender gap can extend to the lack of equal representation in certain industries or career paths, and there's an extraordinarily long way to go before people will be on equal footing in the labor market. Human resources professionals can rely on data analytics to make progress.

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How to Drive Cost Savings, Efficiency Gains, and Sustainability Wins with MES

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

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Top Stories, Dec 16-29: What is a Data Scientist Worth?; Google’s New Explainable AI Service

KDnuggets

Also: Let’s Build an Intelligent Chatbot; 10 Best and Free Machine Learning Courses, Online; Build Pipelines with Pandas Using pdpipe; Alternative Cloud Hosted Data Science Environments.

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Why Kaggle will not Make you a Great Data Scientist

Teradata

Are you a budding data scientist? Learn why Kaggle only offers a limited view of data science and is not the optimal place to learn data science skills.