March, 2019

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Computer Vision Tutorial: A Step-by-Step Introduction to Image Segmentation Techniques (Part 1)

Analytics Vidhya

Introduction What’s the first thing you do when you’re attempting to cross the road? We typically look left and right, take stock of the. The post Computer Vision Tutorial: A Step-by-Step Introduction to Image Segmentation Techniques (Part 1) appeared first on Analytics Vidhya.

Analytics 307
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Data’s Growing Role in Scalable Ecommerce?

Dataconomy

Here is how Big Data can help you in your growth strategies in ecommerce Ecommerce is taking a bigger slice of the global retail pie. In the US, for example, ecommerce currently accounts for approximately 10% of all retail sales, a number that’s projected to swell to nearly 18% by. The post Data’s Growing Role in Scalable Ecommerce? appeared first on Dataconomy.

Big Data 195
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DATAx - A Production ML system for SEA's Biggest Hospital Group

Eugene Yan

How we built an ML system to predict hospitalization costs at admission; sharing at DATAx Conference.

ML 130
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How to Achieve Consistent Quality in AI

DataRobot

AI has tremendous potential for benefiting humanity in every area of how we live and work. While most people realize this fact, their hopes for AI also come with a note of caution. A recent survey reported that 77% of Americans expressed that AI would have a “very positive” or “mostly positive” impact on how people work and live in the next 10 years.

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Optimizing The Modern Developer Experience with Coder

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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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.

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Complete ML Study Path On Github

Data Science 101

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.

ML 105
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How Financial Institutions Are Becoming Champions Of Big Data

Smart Data Collective

If someone asked you which industry is the most innovative , you probably wouldn’t say the financial industry. In fact, that would probably be the last industry on your list. Nonetheless, the financial industry is using big data more than ever. The success of both Fintech companies and traditional banks will hinge on their ability to leverage big data to its fullest potential.

Big Data 101

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Why There Are IT Outages – And What to Do About Them?

Dataconomy

What do fat fingers, power failures, and Godzilla have in common? Answer: They have all been responsible for IT outages that, even if they aren’t caused by Godzilla, can cause monster-sized budget holes for companies. How monster-sized? A Rand Organization report says that according to 98% of organizations, IT outages. The post Why There Are IT Outages – And What to Do About Them?

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Machine Learning for Beginners: An Introduction to Neural Networks

Victor Zhou

Here’s something that might surprise you: neural networks aren’t that complicated! The term “neural network” gets used as a buzzword a lot, but in reality they’re often much simpler than people imagine. This post is intended for complete beginners and assumes ZERO prior knowledge of machine learning. We’ll understand how neural networks work while implementing one from scratch in Python.

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March Madness: How to Up Your Game by Building a Better Bracket

DataRobot

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.

AI 91
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Microsoft Launches Data Science Certifications

Data Science 101

Read to the end to learn more about a new study group I will be launching. In Late January 2019, Microsoft launched 3 new certifications aimed at Data Scientists/Engineers. For a while, Microsoft has been toying with different methods for training and credentials. They launched the Microsoft Professional Program in Data Science back in 2017. While it provides great content, it did not result in either a college diploma or an official Microsoft certification.

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15 Modern Use Cases for Enterprise Business Intelligence

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?

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Your Guide To Understanding Various Types of Data Masking

Smart Data Collective

“Google Search Reveals Community College Student’s Social Security Number.” While this may seem like a headline you would find on sites like The Onion , this is something that actually happened. This situation occurred when staff members at a community college started to test a new type of online application that utilized files full of sensitive and unaltered data on a server that was not secure.

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5 Amazing Deep Learning Frameworks Every Data Scientist Must Know! (with Illustrated Infographic)

Analytics Vidhya

Introduction I have been a programmer since before I can remember. I enjoy writing codes from scratch – this helps me understand that topic. The post 5 Amazing Deep Learning Frameworks Every Data Scientist Must Know! (with Illustrated Infographic) appeared first on Analytics Vidhya.

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How to apply predictive analytics to Premiership football to beat the bookies?

Dataconomy

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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The Intuition behind Adversarial Attacks on Neural Networks

ML Review

Are the machine learning models we use intrinsically flawed? What are adversarial attacks? In 2014, a group of researchers at Google and NYU found that it was far too easy to fool ConvNets with an imperceivable, but carefully constructed nudge in the input. Up to this point, machine learning algorithms simply didn’t work well enough for anyone to be surprised when it failed to do the right thing.

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Marketing Operations in 2025: A New Framework for Success

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.

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Ruthlessly Practical: Turning Busy Work into Brain Work for Your Data Science Team

DataRobot

Data scientist time is a precious, expensive commodity. Do you truly understand what your data science talent works on all day? Are they spending way too much time researching data science theory, coding the same data preparation tasks over and over again, and maintaining scripts for model factories? Take a serious look at what your data scientists actually do.

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Machine Learning for Kids

Data Science 101

Machine Learning for Kids is a site for children and teachers to explore machine learning with the Scratch Programming language. It includes numerous lessons and tutorials for building fun programs which incorporate machine learning.

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Optimizing the IoT Infrastructure for Enhanced Big Data Performance

Smart Data Collective

The Internet of Things is one of the most groundbreaking trends affecting consumers and businesses all over the world. According to a report by Gartner, the economic impact of all products connected to the IoT will exceed $300 billion by next year. A number of factors are contributing to the proliferation of the IoT. One of the most influential changes is the increasing capacity of big data.

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A Step-by-Step NLP Guide to Learn ELMo for Extracting Features from Text

Analytics Vidhya

Introduction I work on different Natural Language Processing (NLP) problems (the perks of being a data scientist!). Each NLP problem is a unique challenge in. The post A Step-by-Step NLP Guide to Learn ELMo for Extracting Features from Text appeared first on Analytics Vidhya.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

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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C-Suite Whispers: Considering an event-centric data strategy? Here’s what you need to know

Dataconomy

Digital transformation dominates most CIO priority lists pertaining to questions such as: How will digital transformation affect IT infrastructure? Will technology live on-premise or in the cloud? Depending on where that data lives, an organization requires different skill sets. If you’re building these resources in-house, then you need an infrastructure.

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A Simple Explanation of Gini Impurity

Victor Zhou

If you look at the documentation for the DecisionTreeClassifier class in scikit-learn , you’ll see something like this for the criterion parameter: The RandomForestClassifier documentation says the same thing. Both mention that the default criterion is “gini” for the Gini Impurity. What is that?! TLDR: Read the Recap. Decision Trees ? Training a decision tree consists of iteratively splitting the current data into two branches.

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Game-Changing Analytics: How the Philadelphia 76ers Scored Big Wins Off the Court

DataRobot

For the Philadelphia 76ers, data is an integral part of how they work, helping them make strategic decisions on both the sports and corporate sides of the organization. On the business side, they knew that taking a data-driven approach could help them become much more efficient in how they approach their ticket sales process. Enter automated machine learning with the layup.

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Free Data Science University Course Notes

Data Science 101

University can be a great way to learn data science. However, many universities are very expensive, difficult to get admitted, or not geographically feasible. Luckily, a few of them are willing to share data science, machine learning and deep learning materials online for everyone. Here is just I small list I have come across lately. MIT Deep Learning – Lecture notes, slides and guest talks about deep learning and self driving cars Introduction to Artificial Intelligence from UC Berkeley &

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How to Drive Cost Savings, Efficiency Gains, and Sustainability Wins with MES

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

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Why Data Analytics In The Insurance Industry Is A Major Game Changer

Smart Data Collective

Technology has had a profound impact on the insurance industry. Insurers are relying heavily on big data as the number of insurance policyholders also grow. Big data analytics can help solve a lot of data issues that insurance companies face, but the process is a bit daunting. It can be challenging for insurance companies who have not adjusted to this just yet.

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16 OpenCV Functions to Start your Computer Vision journey (with Python code)

Analytics Vidhya

Introduction Computer vision is among the hottest fields in any industry right now. It is thriving thanks to the rapid advances in technology and. The post 16 OpenCV Functions to Start your Computer Vision journey (with Python code) appeared first on Analytics Vidhya.

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How Agile Cloud Solutions Can Upgrade On-Prem Performance: The BI Business Case?

Dataconomy

Moving IT to the cloud is one of the main objectives for many companies. But once achieved, they find managing data in a hybrid environment a challenge. This is when metadata management becomes more important than ever. Cloud vs. on-premises? It’s one of those topics that you hear broached at. The post How Agile Cloud Solutions Can Upgrade On-Prem Performance: The BI Business Case?

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My First 50 Days of Blogging

Victor Zhou

Why? I started this blog at the beginning of last month (February 2019) because I wanted to become a better writer. I felt like I had some interesting/useful things to say. I’d sold both of my main side projects and wanted a new challenge. I didn’t like the old victorzhou.com and had been itching to rewrite it for a while. I wanted to learn more about and get firsthand experience with SEO.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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Our Obsession with Continuous Testing

DataRobot

In a previous blog post , we introduced you to Zach Deane-Mayer, a data scientist who runs our core modeling team. One of the most important tools in his team’s arsenal is a data science performance evaluation system created and maintained by our QA team. This system is at the core of our comprehensive testing philosophy that we believe is crucial to delivering a platform that our customers can trust, no matter what DataRobot features they’re using or how they’ve chosen to deploy them.

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3 Tips for Data Science Interviews

Data Science 101

1. Be Honest. Try not to exaggerate your skills. If the job sounds more engineering focused than you are wanting, be honest and say that. Data Science is getting very broad and you don’t want to get in a position that is a bad fit. You often sound worse when you try to explain something you do not understand. Just be honest and say, “I have not needed to use that yet, can you explain to me when you have done that?

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Big Data is Transforming the Future of WordPress Hosting

Smart Data Collective

Forbes contributor Kalev Leetaru recently wrote a fantastic article about the intersection of big data and website hosting. Leetaru notes that big data and cloud technology have led to the evolution of web hosting services. Cloud technology is changing the logistics of many traditional hosting plans. WordPress hosting is a prime example. How Big Data is Changing the Future of WordPress.

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8 Excellent Pretrained Models to get you Started with Natural Language Processing (NLP)

Analytics Vidhya

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.

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The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.