Dataiku
DECEMBER 13, 2019
New types of data, tools, and technologies are shaping the jobs of analysts, taking them in exciting new directions. In fact, things are moving so fast in the data analytics space, that some analysts are beginning to worry about what this could mean for the future of their jobs.
erwin
DECEMBER 12, 2019
Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance. So most early-stage data governance managers kick off a series of projects to profile data, make inferences about data element structure and format, and store the presumptive metad
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Analytics Vidhya
DECEMBER 10, 2019
Overview The rise of artificial intelligence (AI) has disrupted many industries in recent years One of the most impacted industries – retail! Retail operations. The post 10 Exciting Real-World Applications of AI in Retail appeared first on Analytics Vidhya.
Corinium
DECEMBER 9, 2019
AI is now well into its ‘early adoption’ phase, with businesses throughout the Middle East and Africa clamoring to launch new initiatives.
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.
O'Reilly on Data
DECEMBER 10, 2019
Roughly a year ago, we wrote “ What machine learning means for software development.” In that article, we talked about Andrej Karpathy’s concept of Software 2.0. Karpathy argues that we’re at the beginning of a profound change in the way software is developed. Up until now, we’ve built systems by carefully and painstakingly telling systems exactly what to do, instruction by instruction.
Data Science 101
DECEMBER 12, 2019
It is Computer Science Education Week and in 2019 Machine Learning and Artificial Intelligence are two of the most popular and influential topics in technology. That is why I was so excited when Code.org launched a training specifically aimed at the topics. It is called AI for Oceans and it is geared for children (or really anyone, I had fun with it and so did my children).
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Corinium
DECEMBER 12, 2019
“There’s no gender bias in our process for extending credit,” Goldman Sachs CEO David Solomon insisted in a recent TV interview. “We don’t ask, when someone applies, if they’re a man of a woman.”.
O'Reilly on Data
DECEMBER 12, 2019
For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML. Without being able to troubleshoot models when they underperform or misbehave, organizations simply won’t be able to adopt and deploy ML at scale.
KDnuggets
DECEMBER 12, 2019
Python's plotting libraries such as matplotlib and seaborn does allow the user to create elegant graphics as well, but lack of a standardized syntax for implementing the grammar of graphics compared to the simple, readable and layering approach of ggplot2 in R makes it more difficult to implement in Python.
Analytics Vidhya
DECEMBER 8, 2019
Overview Feature engineering is a skill every data scientist should know how to perform, especially in the case of time series We’ll discuss 6. The post 6 Powerful Feature Engineering Techniques For Time Series Data (using Python) appeared first on Analytics Vidhya.
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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?
Corinium
DECEMBER 10, 2019
Navigating A Digital World.
Jet Global
DECEMBER 13, 2019
It’s easy to think of enterprise performance reporting as a necessary evil. Companies need reports to evaluate their success objectively and plan their next move strategically. Yet reporting is a complex, time-consuming process that can leave those responsible feeling frustrated by how much effort is involved. PeopleSoft is a valuable tool for enterprise data collection, full of insights companies need to find and leverage.
KDnuggets
DECEMBER 10, 2019
From not sweating missing values, to determining feature importance for any estimator, to support for stacking, and a new plotting API, here are 5 new features of the latest release of Scikit-learn which deserve your attention.
Analytics Vidhya
DECEMBER 9, 2019
Overview Game Theory can be incredibly helpful for decision making in competitive scenarios Understand the concept of Normal Form Games in the context of. The post Game Theory 101: Decision Making in a Competitive Scenario using Normal Form Games appeared first on Analytics Vidhya.
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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.
FineReport
DECEMBER 11, 2019
In the past few years, the term “data science” has been widely used, and people seem to see it in every field. “Big Data”, “Business Intelligence”, “ Data Analysis ” and “ Artificial Intelligence ” came into being. For a while, everyone seems to have begun to learn data analysis. However, before you get started, you can’t help but ask questions: is it suitable for me to learn data analysis?
Jet Global
DECEMBER 11, 2019
Compliance is complicated. That’s the sentiment echoed by 800 senior compliance officers responding to a Thompson Reuters survey. When asked to rank their top challenges, most put managing continuing compliance changes at the top of the list. Every year, regulatory frameworks ranging from Sarbanes Oxley to the NCAA rules undergo updates and revisions.
KDnuggets
DECEMBER 9, 2019
The field of Data Science is growing with new capabilities and reach into every industry. With digital transformations occurring in organizations around the world, 2019 included trends of more companies leveraging more data to make better decisions. Check out these next trends in Data Science expected to take off in 2020.
Sisense
DECEMBER 9, 2019
Blog. Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. Our BI Best Practices demystify the analytics world and empower you with actionable how-to guidance. Preserving insights. One of the biggest pitfalls in data is the preservation of insights when analysis is handed off from the data team to a business professional.
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.
DataRobot
DECEMBER 7, 2019
This blog provides a unique take on using machine learning to predict free agent signings in the off-season. MLB’s Hot Stove season has begun and several big contracts have already been handed out to Zack Wheeler, Yasmani Grandal, Will Smith, and more. However, over 90% of this year’s free agent class remains unsigned, including the big three of Gerritt Cole, Stephen Strasburg, and Anthony Rendon.
MLWhiz
DECEMBER 8, 2019
Algorithms are an integral part of data science. While most of us data scientists don’t take a proper algorithms course while studying, they are important all the same. Many companies ask data structures and algorithms as part of their interview process for hiring data scientists. Now the question that many people ask here is what is the use of asking a data scientist such questions.
KDnuggets
DECEMBER 13, 2019
We show how to build intuitive and useful pipelines with Pandas DataFrame using a wonderful little library called pdpipe.
Jet Global
DECEMBER 12, 2019
It’s that time of year again. Yes, year-end reporting and setting everything up for next year. But we mean the holidays, and what better way to get in the “spirit” of all things data than by toasting with our exclusive Holiday Cocktail Generator! We’ve put our Excel skills to very good use to help you drill down into the perfect holiday beverage by filtering for the type of drink you like, what you want it in, even the kind of glass you have on hand.
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.
erwin
DECEMBER 12, 2019
Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance. So most early-stage data governance managers kick off a series of projects to profile data, make inferences about data element structure and format, and store the presumptive metad
Bruno Aziza
DECEMBER 8, 2019
Ten years ago, I invited the community to envision the future of Data, AI and Analytics. From Paris, I asked: what could the world of AI, Data and Analytics look like by 2020?! This past month, I drove down to Silicon Valley’s Computer History Museum and asked again.
KDnuggets
DECEMBER 11, 2019
We asked leading experts - what are the most important developments of 2019 and 2020 key trends in AI, Analytics, Machine Learning, Data Science, and Deep Learning? This blog focuses mainly on technology and deployment.
Data Science 101
DECEMBER 11, 2019
This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). Every year they host an excellent and influential conference focusing on many areas of data science. Honestly, KDD has been promoting data science way before data science was even cool. 1989 to be exact. They have opened a call for papers for the 2020 conference. The details are below.
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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.
Depict Data Studio
DECEMBER 10, 2019
You eavesdrop too, right? It’s hard to avoid. I overheard a conversation at a conference lunch table recently. It went something like this: Smart, hardworking person #1: I love the idea of using data to drive decisions, but spreadsheets can be such a drag. It takes forever to finish all the monthly reports that my organization is required to submit.
IBM Big Data Hub
DECEMBER 10, 2019
Global data privacy compliance regulations like the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA) a nd Brazil’s LGPD have created scrutiny around personal, customer and employee data.
KDnuggets
DECEMBER 12, 2019
The speed at which AI made advancements and news during 2019 makes it imperative now to step back and place these events into order and perspective. It's important to separate the interest that any one advancement initially attracts, from its actual gravity and its consequential influence on the field. This review unfolds the parallel threads of these AI stories over this year and isolates their significance.
Data Science 101
DECEMBER 9, 2019
In case you don’t have time or the patience to read the entire post, Cloud Data Science News – Beta #5 ; you can watch the quick 60 second overview. Tons of machine learning news out of Amazon AWS. If you would like to get the updates as a weekly email, you sign up for the Newsletter.
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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