Analytics Vidhya
MARCH 21, 2019
Introduction Do you often work with reports in Excel? Or regularly build dashboards and visualizations in Tableau or Power BI? If you answered yes. The post Infographic: 11 Steps to Transition into Data Science (for Reporting / MIS / BI Professionals) appeared first on Analytics Vidhya.
Dataconomy
MARCH 19, 2019
A few years ago, I combined my day job as a data engineer, helping customers engineer data analytics, with my love for football and set out to beat the bookies. It’s an exciting game to play, and I have learned a lot about the merits of different predictive models that. The post How to apply predictive analytics to Premiership football to beat the bookies?
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Data Science 101
MARCH 16, 2019
Recently updated, is the March 2019 Machine Learning Study Path. It contains links and resources to learn Tensorflow and Scikit-Learn. If you are interested in details on the study path and how to best use the resources. There is a livestream on Facebook, Sunday March 17 on the Math for Data Science Facebook page.
DataRobot
MARCH 20, 2019
The 2019 NCAA March Madness tournament has arrived! This is one of the most famous annual sports events in the United States, bringing together the best Division 1 men’s and women’s college basketball teams from 68 schools to compete against each other for the NCAA Champion title.
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Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.
Analytics Vidhya
MARCH 17, 2019
Introduction Natural Language Processing (NLP) applications have become ubiquitous these days. I seem to stumble across websites and applications regularly that are leveraging NLP. The post 8 Excellent Pretrained Models to get you Started with Natural Language Processing (NLP) appeared first on Analytics Vidhya.
Smart Data Collective
MARCH 21, 2019
Among the various factors that play a role in the content marketing decision-making process, analytics ranks near the top of the list. However, not many people understand the benefits of using various analytics tools for marketing a business. Two Experts Share their Perspective on the Benefits of Analytics in Marketing. Elissa Hudson has covered the importance of analytics in digital marketing in her post for HubSpot.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Data Elixir
MARCH 21, 2019
Welcome to Data Elixir! The Data Elixir newsletter goes out once a week on Tuesdays. In the meantime, a link to the latest issue has already been sent to your email address. If you don’t see that email, please check your “Promotions” tab or Spam folder and if you find it there, drag it to your Inbox. If you have a moment, please select your interests >> Thanks for joining!
Analytics Vidhya
MARCH 19, 2019
Introduction How do we build interpretable machine learning models? Or, in other words, how do we build trust in the models we design? This. The post DataHack Radio #20: Building Interpretable Machine Learning Models with Christoph Molnar appeared first on Analytics Vidhya.
Smart Data Collective
MARCH 22, 2019
Big data has made its way into virtually every industry. The real estate profession is no exception. Real estate professionals all over the world are benefiting from big data in a number of ways. CIO has published a very introspective article on eight companies that are using big data to disrupt the real estate industry. Here are some of the biggest benefits of big data for real estate.
Explosion
MARCH 17, 2019
Version 2.1 of the spaCy Natural Language Processing library includes a huge number of features, improvements and bug fixes. In this post, we highlight some of the things we're especially pleased with, and explain some of the most challenging parts of preparing this big release.
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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?
DataCentric podcast
MARCH 18, 2019
The latest server and storage market numbers are out, and there are some big winners. And some big losers. Matt & Steve go all "inside-baseball" and talk about what it all means. They also touch on recent news around NVIDIA's Mellanox acquisition, Intel's CXL consortium, and the momentum of the Chinese technology providers. 01:30 IDC Releases 4Q2018 Server Market Numbers 06:08 What's it mean for the HyperScalers?
DataRobot
MARCH 22, 2019
What stories are the most compelling? What plot lines are resonating with audiences the most?
Smart Data Collective
MARCH 21, 2019
Trying to create the ultimate SaaS pricing strategy is tricky, to say the least. The point is to make yourself and your customers happy – you want your product to be properly aligned with value so you can earn revenues from it, while on the other side clients want something they deem “affordable.” If the price is too low, it may even deter the buyers as it may be associated with low quality.
Data Elixir
MARCH 21, 2019
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Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com
Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.
Smart Data Collective
MARCH 22, 2019
There are countless applications of machine learning in 2019. The demand for machine learning developers is growing at a rapid pace. MIT recently announced that it is committing $1 billion to a new program to educate technology professionals about machine learning and artificial intelligence. New academic programs are likely to be launched to focus on this rapidly growing field.
Smart Data Collective
MARCH 21, 2019
Data is in the air businesses breathe and the water they drink; it is impossible to run a business successfully in 2019 without an ample amount of information about customers, competitors and more. However, too often, businesses make major mistakes when it comes to data collection. It’s possible, easy even, to collect too much data, and oftentimes businesses focus on gathering data that doesn’t do them any good while ignoring types of data that would make a major difference.
Smart Data Collective
MARCH 22, 2019
All technologies today are connected to cloud computing. And unsurprisingly, robotics as well. The biggest beneficiary of this mix of novel and complex technologies seems to be the manufacturing sector. By the end of this year, the global expenditure of robotics and robot-related services will reach approximately $135 bn. As a comparison, the 2015 expenditure of robotics was only $71 bn.
Smart Data Collective
MARCH 22, 2019
Big data is helping online entrepreneurs address some of the most pressing obstacles that they have faced for years. Marketers have utilized deep learning technology to get a better understanding of their customers, so they can refine their creative and targeting strategies. However, there are less obvious applications of big data that are equally important.
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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