Smart Data Collective
OCTOBER 3, 2019
Big data is playing a vital role in the evolution of small business. A compilation of research from the G2 Learning Hub Shows the number of businesses relying on big data is rising. They cited one study showing that 40% of businesses need to use unstructured data on a nearly daily basis. One of the ways that businesses can gain an edge is with digital marketing strategies that hinge on big data.
Peter James Thomas
OCTOBER 1, 2019
Introduction. The recent update of The Data & Analytics Dictionary featured an entry on Charts. Entries in The Dictionary are intended to be relatively brief [1] and also the layout does not allow for many illustrations. Given this, I have used The Dictionary entries as a basis for this slightly expanded article on the subject of chart types. A Chart is a way to organise and Visualise Data with the general objective of making it easier to understand and – in particular – to disc
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Corinium
OCTOBER 3, 2019
The benefits of becoming a data-driven organization are clear. Enterprises that succeed in creating data environments where innovation can flourish tend to have happier customers and generate more revenue as a result.
Analytics Vidhya
OCTOBER 2, 2019
Overview Here are eight ambitious data science projects to add to your data science portfolio We have divided these projects into three categories – The post Add Shine to your Data Science Resume with these 8 Ambitious Projects on GitHub appeared first on Analytics Vidhya.
Speaker: John Mansour
If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.
KDnuggets
OCTOBER 2, 2019
Applying a clustering algorithm is much easier than selecting the best one. Each type offers pros and cons that must be considered if you’re striving for a tidy cluster structure.
DataCamp
OCTOBER 1, 2019
This cheat sheet guides you through the basics of how data science can help your business, including building your data science team and the common steps in the data science workflow.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Analytics Vidhya
SEPTEMBER 29, 2019
Overview Seaborn is a popular data visualization library for Python Seaborn combines aesthetic appeal and technical insights – two crucial cogs in a data. The post Become a Data Visualization Whiz with this Comprehensive Guide to Seaborn in Python appeared first on Analytics Vidhya.
KDnuggets
OCTOBER 2, 2019
As data scientists who are the brains behind the AI-based innovations, you need to understand the significance of data preparation to achieve the desired level of cognitive capability for your models. Let’s begin.
Data Science 101
SEPTEMBER 28, 2019
Amazon and Coursera have teamed up to create Getting Started with AWS Machine Learning. Topics covered are: Machine Learning. Computer Vision. NLP. Amazon Sagemaker. Happy Learning!
Corinium
OCTOBER 2, 2019
C. ustomers demand more instantaneous, personalized attention, and companies are leveraging new technologies that go beyond traditional voice and email customer service channels to meet those demands. But just how meaningful are these experiences on consumer buying behavior? How long does the effect last? Do new technologies and recent cultural. shifts significantly change the way experiences are evaluated?
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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?
Analytics Vidhya
SEPTEMBER 30, 2019
Overview A hands-on tutorial to build your own convolutional neural network (CNN) in PyTorch We will be working on an image classification problem – The post Build an Image Classification Model using Convolutional Neural Networks in PyTorch appeared first on Analytics Vidhya.
KDnuggets
OCTOBER 1, 2019
Data science education in Europe has been reevaluated and new recommendations are leading the way to the next generation of data science Master's courses to better support and train students.
Data Science 101
OCTOBER 2, 2019
A few weeks ago, I attended my first SQLSaturday event. I brought along my camera and was lucky enough to record a couple interviews. This is one of those interviews. I sat down with John Byrnes and we discussed: Where has SQL taken his career? What does the SQLSaturday community mean to him? Why should someone attend a SQLSaturday event? SQLSaturday Interview with John Byrnes.
Corinium
OCTOBER 1, 2019
What are you going to present at Verify 2019? I am looking at the affect we have when we can identify everybody. Does that makes people safer or less safe, particularly vulnerable people? This is a little bit of an unusual topic for an identity conference, but it is an important question that I think will be very interesting.
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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.
Smart Data Collective
OCTOBER 2, 2019
According to a recent Adobe report , marketers have identified data-driven marketing as the most important business opportunity for 2019. That clearly indicates the importance that marketers give to data and why you should too. After all, data-driven marketing can help you achieve numerous benefits for your business, ultimately leading to an increase in conversions.
KDnuggets
SEPTEMBER 30, 2019
This thorough review focuses on the impact of AI, 5G, and edge computing on the healthcare sector in the 2020s as well as a look at quantum computing's potential impact on AI, healthcare, and financial services.
IBM Big Data Hub
OCTOBER 1, 2019
IBM Watson Studio Premium for Cloud Pak for Data includes IBM Decision Optimization, SPSS Modeler and more. Read why you need this for your data. .
TDAN
OCTOBER 1, 2019
Is there a difference between open data and public data? Yes. And it’s a big one. There is a general consensus that when we talk about open data, we are referring to any piece of data or content that is free to access, use, reuse, and redistribute. Due to the way most governments have rolled out […].
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.
Smart Data Collective
OCTOBER 1, 2019
What exactly is artificial intelligence (AI) and what business does it have in higher education? Simply put, AI is an attempt to emulate human knowledge by programming extensive rules into computers. Through machine learning and expert systems, machines can produce patterns within mass flows of data and pinpoint correlations that couldn’t possibly be immediately intuitive to humans.
KDnuggets
OCTOBER 4, 2019
This is it: the last SQL guide for data analysis you'll ever need! OK, maybe it’s actually the first. But it’ll give you a solid head start.
IBM Big Data Hub
OCTOBER 2, 2019
Today, “doing more with less” is a key principle driving business strategy across many resource-intensive industries. Organisations are looking to get more out of artificial intelligence (AI) and machine learning (ML) than just great insights. They need access to recommendations that help simplify complex decisions around how scarce resources should be allocated, how to schedule tasks, and how to deal with constraints.
Sisense
OCTOBER 2, 2019
Blog. Different Business Needs Changes Convergence What to Do Now. Reporting and business intelligence are often used to refer to the same thing — but wrongly so! The difference between reporting and business intelligence goes beyond charts for the first or data correlations for the second. To understand how they compare, it’s best to start with the separate business and end-user needs that each of these two functions is meant to satisfy.
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.
Smart Data Collective
OCTOBER 4, 2019
Smart cities are the future of our urban centers, and even of suburbs and small towns – and this transformation is critical. Equipped with sensors and constantly collecting data, this tech revolution aims to make crowded cities more efficient, keep residents safer, and even help protect our environment through resource management. Making this shift, however, will require big investments on the part of both government bodies and businesses.
KDnuggets
SEPTEMBER 30, 2019
Three new releases that will help researchers streamline the implementation of reinforcement learning programs.
IBM Big Data Hub
OCTOBER 3, 2019
Today’s data science and analytics teams are often composed of individuals with a variety of skill sets, educational backgrounds, levels of exposure to open source tools and professional needs.
Insight
OCTOBER 4, 2019
This comprehensive and easy three-step tutorial lets you train your own custom image detector using YOLOv3. The only requirement is basic familiarity with Python. Our input data set are images of cats (without annotations). As an example, we learn how to detect faces of cats in cat pictures. Given the omnipresence of cat pictures on the internet, this is clearly a long-awaited and extremely important feature!
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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.
Smart Data Collective
SEPTEMBER 30, 2019
Big data is making a number of cybersecurity risks worse than ever. A growing number of companies are starting to explore the need to utilize big data to enhance their digital security. They are also starting to recognize that hackers are using big data as well, so they need to monitor them carefully. One of the biggest areas that they need to address is password security.
KDnuggets
OCTOBER 3, 2019
There is no clear outline on how to study Machine Learning/Deep Learning due to which many individuals apply all the possible algorithms that they have heard of and hope that one of implemented algorithms work for their problem in hand. Below, I've listed out some of the steps that one should adopt while solving a machine learning problem.
TDAN
OCTOBER 1, 2019
Become a “Data-First” Company The organizations that invest in data first and foremost are changing the business landscape. Apple had famously reached a trillion dollar valuation on August 2, 2018, and analysts predicted that Amazon wasn’t far behind. The race to a trillion mimics the 4 minute mile; as soon as one person breaks it, […].
Domino Data Lab
OCTOBER 2, 2019
This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications by Andrew Kelleher and Adam Kelleher. A complementary Domino project is available. . Introduction. As data science work is experimental and probabilistic in nature, data scientists are often faced with making inferences.
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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