Analytics Vidhya
AUGUST 6, 2020
Overview Open-source data science projects are a great way to prepare yourself for the future. Explore the open-source data science projects from computer vision, The post 6 Open-Source Projects to Become Future-Ready Data Scientist appeared first on Analytics Vidhya.
Dataconomy
AUGUST 6, 2020
Professional sports lend themselves really well to economic calculations – players, coaches, and agents act similarly to the hypothetical, rational decision-makers in economic models. While this data may seem complex or hard to obtain, it’s actually all readily available online – you just need to know where to look, how. The post Every deal in professional sports is based on data appeared first on Dataconomy.
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Hacker News
AUGUST 4, 2020
Over the last few months, my colleague Unmesh Joshi has been running workshops to teach developers about distributed systems design. In this work he's been delving into many open-source distributed systems and identifying patterns. As he writes them up, he's publishing the patterns on my site. Today he's publishing an initial narrative article that ties the first batch of patterns together, and two of these patterns: Heartbeat and Generation Clock.
Smart Data Collective
AUGUST 4, 2020
Digital marketing is becoming more important during the pandemic. One study in the UK found that 65% of consumers increased spending during the crisis. Companies are investing more in digital marketing to respond to changing consumer behavior. Unfortunately, they have also found it difficult to train employees. Fortunately, new data analytics advances can help.
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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
AUGUST 2, 2020
So Overview Understand the concept of Non-Max Suppression Learn how object detection algorithms use Non-Max Suppression Implement non-max suppression using NMS function in PyTorch. The post Selecting the Right Bounding Box Using Non-Max Suppression (with implementation) appeared first on Analytics Vidhya.
Dataconomy
AUGUST 4, 2020
BI can help you start making sense of your data, but it still expects you to do the heavy lifting when it comes to finding insights. Building predictive models that can cut down your decision time and offer better insights is a must, but achieving them sounds impossible. So, why. The post AI is Making BI Obsolete, and Machine Learning is Leading the Way appeared first on Dataconomy.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Smart Data Collective
AUGUST 4, 2020
The big data market is exploding. According to Markets and Markets, it will be worth $229 billion in the next five years. Despite the rapid evolution of big data, many small businesses are overlooking its benefits. You should not make this mistake. You should consider the vast benefits of big data and invest in it accordingly. Why Small Businesses Overlook Big Data (And Should Start Embracing it).
Analytics Vidhya
AUGUST 5, 2020
Overview Text analytics is becoming easier with many people working day and night on each aspect of Natural Language Processing We list a set. The post People to Follow in the field of Natural Language Processing (NLP) appeared first on Analytics Vidhya.
Dataconomy
AUGUST 4, 2020
To guide your company towards success, leaders need a clear idea of what’s around the corner. It’s not enough to analyze what happened in the past. You need to know what the future holds. And that means data science-backed predictive models. More data science doesn’t always mean more data scientists, though. The post FREE GUIDE: Do You Need a Data Science Team, Platform, or Service?
Eugene Yan
AUGUST 4, 2020
Updating our FastAPI app to let users select options and download results.
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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
AUGUST 5, 2020
In this writing, readers will get to know in what way AI might replace the key procedures in the judicial system around the world. Additionally, you will get informed in detail concerning the following issues: How AI is being used in judicial systems in the US and China nowadays; Can AI ever make the right decisions and release fair verdicts; Whether it is real that AI will once replace human judges in courts.
Analytics Vidhya
AUGUST 4, 2020
Overview Understand the importance of Time Intelligence functions in Power BI Implement Time Intelligence functions in Power BI with a simple example Introduction. The post Time Intelligence in Power BI: Capitalize on time appeared first on Analytics Vidhya.
The Data Governance Institute
AUGUST 7, 2020
This type of program typically comes into existence because of issues around the quality, integrity, or usability of data. It may be sponsored by a Data Quality group or a business team that needs better quality data. (For example: Data Acquisition or Mergers & Acquisitions.) These types of programs almost always involve Data Quality software, which may be used by business staff, technical staff, Data Stewards, Data Governance teams, or others.
Victor Zhou
AUGUST 3, 2020
Keras is a simple-to-use but powerful deep learning library for Python. In this post, we’ll build a simple Recurrent Neural Network (RNN) and train it to solve a real problem with Keras. This post is intended for complete beginners to Keras but does assume a basic background knowledge of RNNs. My introduction to Recurrent Neural Networks covers everything you need to know (and more) for this post - read that first if necessary.
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
AUGUST 6, 2020
To this day, roughly 90 percent of the world’s trade is handled by the international shipping industry. Not only does this make it one of the most lucrative sectors in the global economy, but as a result, it’s one of the biggest targets for cyber criminals. In order to stay safe, maritime organizations must invest in the proper security mechanisms and strategies.
Analytics Vidhya
AUGUST 4, 2020
Object Detection is a computer vision task in which you build ML models to quickly detect various objects in images, and predict a class. The post Playing with YOLO v1 on Google Colab appeared first on Analytics Vidhya.
The Data Governance Institute
AUGUST 7, 2020
This type of program typically comes into existence because of concerns about Data Information Security controls, or compliance. Compliance, in this context, may refer to regulatory compliance, contractual compliance, or compliance with internal requirements. This focus is often seen combined with a focus on policy enforcement. It’s also seen combined with a focus on Data Quality.
Twilio Segment
AUGUST 3, 2020
There are now 8,000 martech tools available. Which ones should you choose? Our new guide will help you decide which ones are right for your business.
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
AUGUST 6, 2020
At Smart Data Collective, we have talked about a few impressive technological trends that are shaping modern business in the 21st-century. One of the most significant developments that we discuss constantly is the proliferation of artificial intelligence. Video marketing is another major technological breakthrough that is proving to pay massive dividends.
Analytics Vidhya
AUGUST 3, 2020
Overview Introduction to Natural Language Generation (NLG) and related things- Data Preparation Training Neural Language Models Build a Natural Language Generation System using PyTorch. The post Build a Natural Language Generation (NLG) System using PyTorch appeared first on Analytics Vidhya.
The Data Governance Institute
AUGUST 7, 2020
This type of program typically comes into existence in conjunction with a major system acquisition, development effort, or update that requires new levels of cross-functional decision-making and accountabilities. What other types of groups and initiatives might want such a program focus? Enterprise initiatives such as A move to Service Oriented Architecture (SOA), with its need for well-governed data A new focus on Metadata A Master Data Management (MDM) initiative Enterprise Data Management (ED
DataCentric podcast
AUGUST 3, 2020
Earnings for 2Q have started rolling in, with IBM, AMD, and Intel all early reporters from the Data Center world. There's solid financial news for all three, but each with different industry-level impacts. Hosts Matt Kimball & Steve McDowell, both from Moor Insights & Strategy, talk about what it all means. Intel delivered solid numbers, but were punished by both guidance and disclosure of some execution problems in rolling out its next generation, 7nm, processors.
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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.
Hacker News
AUGUST 6, 2020
There are tens of thousands of genes in the human genome: minuscule twists of DNA and RNA that combine to express all of the traits and characteristics that make each of us unique. Each gene is given a name and alphanumeric code, known as a symbol, which scientists use to coordinate research. But over the past year or so, some 27 human genes have been renamed, all because Microsoft Excel kept misreading their symbols as dates.
Analytics Vidhya
AUGUST 7, 2020
Introduction Natural Language Processing (NLP) is one of the most important fields of study and research in today’s world. It has many applications in. The post How to Use Texthero to Prepare a Text-based Dataset for Your NLP Project appeared first on Analytics Vidhya.
The Data Governance Institute
AUGUST 7, 2020
This type of program typically comes into existence in conjunction with a specific data warehouse, data mart, or BI tool. These types of efforts require tough data-related decisions, so organizations often implement governance to help make initial decisions, to support follow-on decisions, and to enforce standards and rules after the new system becomes operational.
Analytics Vidhya
AUGUST 5, 2020
Introduction There are almost 100 python packages being created each day. On PyPI, at the time of writing this article, there are 254,216 projects. The post 7 Awesome Python Packages and Example Projects to Build! appeared first on Analytics Vidhya.
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.
The Data Governance Institute
AUGUST 7, 2020
This type of program typically comes into existence when managers find it difficult to make “routine” data-related management decisions because of their potential effect on operations or compliance efforts. Managers may realize they need to come together to make collaborative decisions but either don’t know all the stakeholders to involve or have an obstacle to assembling them.
The Data Governance Institute
AUGUST 6, 2020
It seems like there are two types of Data Governance and Stewardship programs: 1) Thriving ones, with highly-engaged stakeholders, and 2) Ones whose futures are in question, since stakeholders and stewards are only sporadically involved or give only weak support to the program. “How can I make my stewards come to council meetings?” I’m sometimes asked, and my truthful reply is that you can’t – at least not in a sustainable fashion.
The Data Governance Institute
AUGUST 6, 2020
Most organizations have string change management – or at least change control – mechanisms for technology. They usually have change management for software applications. They have change management for websites. And yet, many organizations do not practice structured change management for data. Why is this important? Some types of data – master data and reference data – should have tightly controlled sets of valid values.
The Data Governance Institute
AUGUST 6, 2020
Remember our (long) definition for Data Governance? “Data Governance is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.” Yes, Data Governance is about enforcing rules.
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.
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