Sat.Nov 23, 2019 - Fri.Nov 29, 2019

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Open Source Projects by Google, Uber and Facebook for Data Science and AI

KDnuggets

Open source is becoming the standard for sharing and improving technology. Some of the largest organizations in the world namely: Google, Facebook and Uber are open sourcing their own technologies that they use in their workflow to the public.

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What is the Chi-Square Test and How Does it Work? An Intuitive Explanation with R Code

Analytics Vidhya

Overview What is the chi-square test? How does it work? Learn about the different types of Chi-Square tests and where and when you should. The post What is the Chi-Square Test and How Does it Work? An Intuitive Explanation with R Code appeared first on Analytics Vidhya.

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Here is how IBM’s Data Scientists look at Data-Driven Future

Dataconomy

An aspiration to create a data-driven future has resulted in massive data lakes, where even the most experienced data scientists can drown in. Today, it’s all about what you do with that data that determines your success. And IBM has the recipe for this. Read on. “Without data, you simply can’t. The post Here is how IBM’s Data Scientists look at Data-Driven Future appeared first on Dataconomy.

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IADSS Talk – Who can be a Data Scientist?

Data Science 101

Initiative for Analytics and Data Science Standards (IADSS) is an organization working to develop standards around the roles in data science. They did a large survey earlier this year and they are starting to role out some of their results. Below is a video with some early results. Great Stuff! Data Science 101 is proud to be an IADSS Digital Community Partner.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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Getting Started with Automated Text Summarization

KDnuggets

This article will walk through an extractive text summarization process, using a simple word frequency approach, implemented in Python.

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A Unique Method for Machine Learning Interpretability: Game Theory & Shapley Values!

Analytics Vidhya

Overview Learn how to use Shapley values in game theory for machine learning interpretability It’s a unique and different perspective to interpret black-box machine. The post A Unique Method for Machine Learning Interpretability: Game Theory & Shapley Values! appeared first on Analytics Vidhya.

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Cloud Data Science News – Beta #4

Data Science 101

In the United States, it is a holiday week, so the news is pretty limited from many of the big cloud providers. Luckily, Amazon has come through with a flurry of machine learning announcements. Amazon is holding their annual re:Invent Conference next week, so maybe these announcements are precursors to some bigger news next week. We will have to wait and see.

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Top KDnuggets tweets, Nov 20-26: How to Speed up Pandas by 4x with one line of code

KDnuggets

Also: Deep Learning for Image Classification with Less Data; How to Speed up Pandas by 4x with one line of code; 25 Useful #Python Snippets to Help in Your Day-to-Day Work; Automated Machine Learning Project Implementation Complexities.

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Tableau Conference 2019 Starting A New Chapter

DataRobot Blog

by Jen Underwood. And so it begins…Tableau enters the Salesforce era. This year Tableau Conference, the world’s largest gathering of data enthusiasts, continued to grow with over 18,000 attendees joining the party in. Read More.

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Get Ready For These Six 2020 Business Intelligence Trends

Smart Data Collective

More and more often, businesses are using data to drive their decisions — which makes cutting-edge analytics and business intelligence strategies one of the best advantages a company can have. New technologies, especially those driven by artificial intelligence (or AI), are changing how businesses collect and extract usable insights from data. Here are the six trends you should be aware of that will reshape business intelligence in 2020 and throughout the new decade. 1.

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Get Better Network Graphs & Save Analysts Time

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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Challenges of Data Science Projects

Data Science 101

It is no secret that data science is difficult. Companies struggle to succeed with data science projects. Even Gartner predicts that by 2022 only 20% of analytics projects will deliver business value. That means about 80% will fail to deliver value. Thus, companies need to be very careful about running data analytics projects. There are many reasons for the failure of data science projects.

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Two Years In The Life of AI, Machine Learning, Deep Learning and Java

KDnuggets

Where does Java stand in the world of artificial intelligence, machine learning, and deep learning? Learn more about how to do these things in Java, and the libraries and frameworks to use.

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Tableau + AWS: Accelerating your digital transformation with Modern Cloud Analytics

Tableau

Jason Dudek. Senior Partner Development Manager. Kevin Glover. Director, Product Management, Tableau. Spencer Czapiewski. November 25, 2019 - 4:39am. November 22, 2022. According to IDC research , analytics spending on the cloud is growing eight times faster than other deployment types.* Having a comprehensive technology stack in the cloud can support the data integration, self-service analytics, and use cases that businesses need to digitally transform and achieve analytics at scale.

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3 Ways Big Data Is Bringing SEO Out of The Stone Age

Smart Data Collective

Anybody that was online in the 1990s knows how different search engines are in the field of SEO. Big data has drastically improved the functionality of search engines. Big data has had a two-pronged effect on the search engine industry. AJ Agrawal, the CEO of Alumnify has talked about this in his article on Inc. Big data is making it a lot easier for search engines to analyze content, which is a great deal for the customer.

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Understanding User Needs and Satisfying Them

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.

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Hey Data People, The NIH needs your help

Data Science 101

The National Institutes of Health (NIH) is creating a Data Management and Sharing Policy. They are currently looking for input on the policy. The NIH funds a lot of research, and this policy will affect the data and results researchers produce. NIH’s DRAFT Data Management and Sharing Policy: We Need to Hear From You! This is the time to share your thoughts.

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A Doomed Marriage of Machine Learning and Agile

KDnuggets

Sebastian Thrun, the founder of Udacity, ruined my machine learning project and wedding.

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Tableau + AWS: Accelerating your digital transformation with Modern Cloud Analytics

Tableau

Jason Dudek. Senior Partner Development Manager. Kevin Glover. Senior Product Manager, Tableau. Spencer Czapiewski. November 25, 2019 - 4:39am. November 16, 2021. According to IDC research , analytics spending on the cloud is growing eight times faster than other deployment types.* Having a comprehensive technology stack in the cloud can support the data integration, self-service analytics, and use cases that businesses need to digitally transform and achieve analytics at scale.

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Can Big Data Eliminate Shortcomings of Team Extension Models?

Smart Data Collective

Big data is becoming more essential in the arena of employee collaboration. A growing number of teams are finding that big data can be very beneficial when it comes to forging stronger relationships between their participants. Dr. Mark van Rijmenam, the founder of DataFlaq is one of the world’s leading experts on the intersection between big data and interpersonal communication.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

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.

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Cluster discovery in german recipes

Depends on the Definition

If you are dealing with a large collections of documents, you will often find yourself in the situation where you are looking for some structure and understanding what is contained in the documents. Here I’ll show you a convenient method for discovering and understanding clusters of text documents.

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Lit BERT: NLP Transfer Learning In 3 Steps

KDnuggets

PyTorch Lightning is a lightweight framework which allows anyone using PyTorch to scale deep learning code easily while making it reproducible. In this tutorial we’ll use Huggingface's implementation of BERT to do a finetuning task in Lightning.

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Tableau + AWS: Accelerating your digital transformation with Modern Cloud Analytics

Tableau

Jason Dudek. Senior Partner Development Manager. Kevin Glover. Senior Product Manager, Tableau. Spencer Czapiewski. November 25, 2019 - 4:39am. November 16, 2021. According to IDC research , analytics spending on the cloud is growing eight times faster than other deployment types.* Having a comprehensive technology stack in the cloud can support the data integration, self-service analytics, and use cases that businesses need to digitally transform and achieve analytics at scale.

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How To Select Ideal SEO Courses In The Big Data Era

Smart Data Collective

Big data is changing the future of the SEO profession. We have witnessed a number of ways that big data can influence the industry. Some of the changes include the following: Big data can be used to identify new link building opportunities through complicated Hadoop data-mining tools. Big data can make it easier to provide a more personalized user experience, which is key to ranking well in Google these days.

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How Embedded Analytics Gets You to Market Faster with a SAAS Offering

Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

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DSAT – First Ever Adaptive Learning Platform for Data Science Professionals

Analytics Vidhya

“Every once in a while, a revolutionary product comes along that changes everything.” – Steve Jobs We are thrilled to announce the launch of. The post DSAT – First Ever Adaptive Learning Platform for Data Science Professionals appeared first on Analytics Vidhya.

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Probability Learning: Naive Bayes

KDnuggets

This post will describe various simplifications of Bayes' Theorem, that make it more practical and applicable to real world problems: these simplifications are known by the name of Naive Bayes. Also, to clarify everything we will see a very illustrative example of how Naive Bayes can be applied for classification.

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AI Simplified: What Computers Are Good At

DataRobot

Is AI taking over our jobs? Will AI replace the need for humans? No. Think of the rise of AI as a way of enhancing us, not replacing us. Colin Priest, VP of AI Strategy at DataRobot, explains when to use AI to complete a task and when to turn to a human.

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Is AI Disrupting the Field of Behavioral Change Marketing?

Smart Data Collective

Artificial intelligence is intended to mimic the behavior of humans. However, AI technology can be applied in reverse – it can be used to change human behavior. There are a number of reasons AI can be great for social engineering, especially in the field of marketing. Julita Vassileva, a Professor at the University of Saskatchewan in Canada wrote a great paper on AI for Human Learning and Behavior.

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Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization

Speaker: Kevin Kai Wong, President of Emergent Energy Solutions

In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.

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Top 8 Data Science Use Cases in Marketing

KDnuggets

In this article, we want to highlight some key data science use cases in marketing. Let us concentrate on several instances that present particular interest and managed to prove their efficiency in the course of time.

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Would you buy insights from this guy? (How to assess and manage a Data Science vendor)

KDnuggets

With all the hype from data science vendors selling "actionable insights" to boost your company's bottom line, selecting your analytics partner should proceed through the same, careful process as any traditional business endeavor. Follow these questions and best practices to ensure you manage accordingly.

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Machine Learning 101: The What, Why, and How of Weighting

KDnuggets

Weighting is a technique for improving models. In this article, learn more about what weighting is, why you should (and shouldn’t) use it, and how to choose optimal weights to minimize business costs.

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Spark NLP 101: LightPipeline

KDnuggets

A Pipeline is specified as a sequence of stages, and each stage is either a Transformer or an Estimator. These stages are run in order, and the input DataFrame is transformed as it passes through each stage. Now let’s see how this can be done in Spark NLP using Annotators and Transformers.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.