Sat.Mar 14, 2020 - Fri.Mar 20, 2020

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TensorFlow 2.0 Tutorial for Deep Learning

Analytics Vidhya

TensorFlow 2.0 – a Major Update for the Deep Learning Community Just when I thought TensorFlow’s market share would be eaten by the emergence. The post TensorFlow 2.0 Tutorial for Deep Learning appeared first on Analytics Vidhya.

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The 4 Best Jupyter Notebook Environments for Deep Learning

KDnuggets

Many cloud providers, and other third-party services, see the value of a Jupyter notebook environment which is why many companies now offer cloud hosted notebooks that are hosted on the cloud. Let's have a look at 3 such environments.

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Calling the global data science community to #HACKCORONA

Dataconomy

COVID-19 is still spreading exponentially throughout the world. Current statistics indicate that 15-20% of people who get it require hospitalization for respiratory failure for multiple weeks. The hardship falls on elderly people, medical personnel as well as the healthcare system in general. Identifying the main pain points in the current. The post Calling the global data science community to #HACKCORONA appeared first on Dataconomy.

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What is the most effective policy response to the new coronavirus pandemic?

Machine Learning (Theory)

Disclaimer: I am not an epidemiologist, but there is an interesting potentially important pattern in the data that seems worth understanding. World healthcare authorities appear to be primarily shifting towards Social Distancing. However, there is potential to pursue a different strategy in the medium term that exploits a vulnerability of this disease: the 5 day incubation time is much longer than a 4 hour detection time.

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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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8 Powerful Hacks to Ace Data Science Hackathons

Analytics Vidhya

Introduction Like any discipline, data science also has a lot of “folk wisdom”. This folk wisdom is hard to teach formally or in a. The post 8 Powerful Hacks to Ace Data Science Hackathons appeared first on Analytics Vidhya.

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What is the most effective policy response to the new coronavirus pandemic?

KDnuggets

Where Test/Trace/Quarantine are working, the number of cases/day have declined empirically. Furthermore, this appears to be a radically superior strategy where it can be deployed. I’ll review the evidence, discuss the other strategies and their consequences, and then discuss what can be done.

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Azure has the most Cloud Regions, and it's not even close

Data Science 101

The big cloud providers are expanding globally by adding more Global Regions. Google recently announced a new mountain west region. Plus, all the other providers have plans to expand globally. This got me wondering, which provider has the most global regions. I went to all the big cloud provider websites, and I was a bit surprised with the results. Google Cloud Regions.

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Top 6 Open Source Pretrained Models for Text Classification you should use

Analytics Vidhya

Introduction We are standing at the intersection of language and machines. I’m fascinated by this topic. Can a machine write as well as Shakespeare? The post Top 6 Open Source Pretrained Models for Text Classification you should use appeared first on Analytics Vidhya.

Analytics 360
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When Will AutoML replace Data Scientists? Poll Results and Analysis

KDnuggets

Will AI always be 5-10 years away? The majority of respondents to this poll think that AutoML will reach expert level in 5-10 years. Interestingly, it is about the same as 5 years ago. We examine the trends by AutoML experience, industry, and region.

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How dangerous news spreads: What makes Twitter users retweet risk-related information

Dataconomy

Scientists uncover how information related to potential dangers can spread on social media and how this can be prevented. In Japan, a country prone to various natural and man-made calamities, users often turn to social media to spread information about risks and warnings. However, to avoid spreading rumors, it is. The post How dangerous news spreads: What makes Twitter users retweet risk-related information appeared first on Dataconomy.

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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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Predicting COVID-19 on the U.S. County Level

DataRobot

With the fight against COVID-19 spreading across the U.S. and the world, DataRobot understands it is essential that federal government entities convey accurate information to citizens, local governments, and healthcare providers. Towards that end, DataRobot’s enterprise AI platform has developed models to predict which U.S. counties are likely to have their first confirmed COVID-19 cases in the next five days.

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What is Multicollinearity? Here’s Everything You Need to Know

Analytics Vidhya

Introduction Multicollinearity might be a handful to pronounce but it’s a topic you should be aware of in the machine learning field. I am. The post What is Multicollinearity? Here’s Everything You Need to Know appeared first on Analytics Vidhya.

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Five Interesting Data Engineering Projects

KDnuggets

As the role of the data engineer continues to grow in the field of data science, so are the many tools being developed to support wrangling all that data. Five of these tools are reviewed here (along with a few bonus tools) that you should pay attention to for your data pipeline work.

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Google Video – Rules of Machine Learning

Data Science 101

To be great with machine learning, it helps to be a great engineer. That means doing the following: write simple code make it readable comment it fix the ever present sign mistake leverage peer review and version control track performance launch and iterate. Those are the general rules for software engineering, this video contains some specific rules for software with machine learning.

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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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Be Humble: Black Swans and the Limits of Inductive Reasoning

DataRobot

After a decade of relative economic stability, we are now confronted by the COVID-19 pandemic, with many financial analysts labelling it as a ‘black swan’ event. A ‘black swan’ is a metaphor for something unexpected which has a major impact. These type of events can cause significant disruption to business processes, financial markets, and our lives.

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Introduction to Polynomial Regression (with Python Implementation)

Analytics Vidhya

Here’s Everything you Need to Get Started with Polynomial Regression What’s the first machine learning algorithm you remember learning? The answer is typically linear. The post Introduction to Polynomial Regression (with Python Implementation) appeared first on Analytics Vidhya.

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A Beginner’s Guide to Data Integration Approaches in Business Intelligence

KDnuggets

An integrated BI system has a trickle-down effect on all business processes, especially reporting and analytics. Find out how integration can help you leverage the power of BI.

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Reasons For Transitioning To Cloud Computing In 2020

Smart Data Collective

Cloud computing has now become a common term that all of us have heard of. However, unfortunately, many of us still don’t understand the complete potential of cloud computing. It is high time for all us to understand how it can make our lives easier. Instead of storing data on a computer or hard drive , cloud computing stores programs and data over the internet.

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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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Cloud Data Science 11

Data Science 101

Even with the coronavirus causing mass closures, there are still some big announcements in the cloud data science world. Google is starting to take enterprise AI seriously and Amazon is continuing to do interesting things. So, here is the news. News. Google introduces Cloud AI Platform Pipelines Google Cloud now provides a way to deploy repeatable machine learning pipelines.

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An Essential Guide to Pretrained Word Embeddings for NLP Practitioners

Analytics Vidhya

Overview Understand the importance of pretrained word embeddings Learn about the two popular types of pretrained word embeddings – Word2Vec and GloVe Compare the. The post An Essential Guide to Pretrained Word Embeddings for NLP Practitioners appeared first on Analytics Vidhya.

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Nine lessons learned during my first year as a Data Scientist

KDnuggets

What is it like to be a Data Scientist? There can be many hats to wear, and so many problems to solve that are fed with data, churned by data science, and guided by business results. Find out about lessons learned from one Data Scientist about how best to work and perform in the role.

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Deciphering Value Points Of Salesforce Einstein Analytics With Big Data

Smart Data Collective

We have written extensively about the benefits of big data in marketing. Louis Columbus wrote a great article in Forbes about 10 ways big data is changing the marketing sector. The business services sector is expected to spend over $77 billion on big data in the near future. Marketing services account for the largest fraction of expenditures here. Salesforce recently created a new product called Einstein Analytics.

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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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Simpler Experimentation with Jupyter, Papermill, and MLflow

Eugene Yan

Automate your experimentation workflow to minimize effort and iterate faster.

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Don't Let a Talent Shortage Stop You from Launching AI & Machine Learning Projects

DataRobot

If you’re not already doing AI, machine learning, or some form of advanced analytical project, research from McKinsey indicates that it’s now or never. Their conclusion, in a nutshell, is that laggards might never be able to catch up to the early adopters. If you’ve got AI or ML projects underway, the next question you can turn your attention to is whether or not those efforts are successful.

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A Comprehensive Data Repository for Fake Health News Detection

KDnuggets

We introduce the FakeHealth, a new data repository for fake health news detection. Following a preliminary analysis to demonstrate its features, we consider additional potential directions for better identifying fake news.

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6 Spectacular Reasons You Must Master the Data Sciences in 2020

Smart Data Collective

The global demand for big data is surging. It will be worth $274 billion within the next two years. It is understandable that many computer science majors are considering pursuing careers in this evolving field. But is it really right for you? Is the Booming Big Data Field Right for You? Everyone has heard about Data Science in 2020. But not many people understand what it really is and how it’s going to change the world.

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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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Azure has the most Cloud Regions, and it’s not even close

Data Science 101

The big cloud providers are expanding globally by adding more Global Regions. Google recently announced a new mountain west region. Plus, all the other providers have plans to expand globally. This got me wondering, which provider has the most global regions. I went to all the big cloud provider websites, and I was a bit surprised with the results. Google Cloud Regions.

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Global Call to Action: COVID-19 Open Research Dataset Challenge (CORD-19)

DataRobot Blog

by Jen Underwood. Today I’m sharing a COVID-19 global call for artificial intelligence talent help from a coalition of leading research groups. Public COVID-19 datasets can be found on Kaggle along with additional. Read More.

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Time Series Classification Synthetic vs Real Financial Time Series

KDnuggets

This article discusses distinguishing between real financial time series and synthetic time series using XGBoost.

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3 Industries Adapting to Major AI Advances in 2020

Smart Data Collective

The market for AI is changing in spectacular ways. It is estimated that the market for artificial intelligence is going to be worth nearly $400 billion by the year 2025. Some industries are driving growth for AI in impressive ways. This is having some major changes on our everyday lives, as well as the operations of many businesses. These days, it seems that human life is becoming more and more intertwined with Artificial Intelligence.

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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.