KDnuggets

SEPTEMBER 9, 2019

This is a collection of 10 interesting resources in the form of articles and tutorials for the aspiring data scientist new to Python, meant to provide both insight and practical instruction when starting on your journey.

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Analytics Vidhya

SEPTEMBER 10, 2019

Overview Sampling is a popular statistical concept – learn how it works in this article We will also talk about eight different types of. The post A Data Scientist’s Guide to 8 Types of Sampling Techniques appeared first on Analytics Vidhya.

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Dataconomy

SEPTEMBER 12, 2019

What is the big problem with the right to be forgotten (right to erasure, Article 17) under the GDPR? As Blockchain generally is immutable, and the GDPR requires personal data to be deleted – many people therefore conclude that it is impossible to store any kind of personal data on. The post Everything you want to know about GDPR’s Right to be Forgotten in Blockchain appeared first on Dataconomy.

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Smart Data Collective

SEPTEMBER 13, 2019

As industry buzzwords, “Big Data” is one of those phrases that has become seemingly ubiquitous. Everyone wants to be using big data to better their operation. The maintenance department is no exception to this trend. Accordingly, maintenance teams are beginning to embrace the use of big data and analytics to improve performance. In emphasizing the use of “big data”, maintenance can establish predictive maintenance programs, which reduce downtime and save on maintenance costs.

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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?

AI

KDnuggets

SEPTEMBER 11, 2019

As compute gets cheaper and time to market for machine learning solutions becomes more critical, we’ve explored options for speeding up model training. One of those solutions is to combine elements from Spark and scikit-learn into our own hybrid solution.

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Analytics Vidhya

SEPTEMBER 8, 2019

Overview Build your own highlights package in Python using a simple approach That’s right – learn how automatic highlight generation works without using machine. The post Become a Video Analysis Expert: A Simple Approach to Automatically Generating Highlights using Python appeared first on Analytics Vidhya.

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Smart Data Collective

SEPTEMBER 13, 2019

Big Data is among one of the most impressive tech advancements that have hit the marketing world in recent memory. While it has been tossed around as a buzzword in certain circles, Big Data is so much more than just a phrase. For a definition , Oracle recommends Gartner’s 2001 description of Big Data, which describes it as data containing a greater variety, getting to the source in increasing volume and at ever-higher velocity.

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KDnuggets

SEPTEMBER 12, 2019

It is important to distinguish prediction and classification. In many decision-making contexts, classification represents a premature decision, because classification combines prediction and decision making and usurps the decision maker in specifying costs of wrong decisions.

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Analytics Vidhya

SEPTEMBER 11, 2019

Overview A data-science-driven product consists of multiple aspects every leader needs to be aware of Machine learning algorithms are one part of a whole. The post 4 Key Aspects of a Data Science Project Every Data Scientist and Leader Should Know appeared first on Analytics Vidhya.

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DataCentric podcast

SEPTEMBER 12, 2019

Want to hear a good origin story? Or about the future of data? You're in luck. As Pure Storage heads into its annual Pure Accelerate Conference in Austin next week, it's looking to celebrate its 10th anniversary. 10 years in which Pure has grown from a seed-stage start-up to a ~$4B publically traded company. And Pure continues to be a disrupter in the storage industry.

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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.

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Smart Data Collective

SEPTEMBER 13, 2019

Gone are the days when storage of information can only be done with the traditional remote servers which are located in a secluded location. Today, the in-thing is cloud data storage where information and data are stored electronically online. With this approach, you can store unlimited data online (in the cloud) and access it anywhere. Several essays and many articles have been written on storage clouds and benefits of the cloud , but this piece puts forward five of the biggest benefits that yo

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KDnuggets

SEPTEMBER 13, 2019

While ensembling techniques are notoriously hard to set up, operate, and explain, with the latest modeling, explainability and monitoring tools, they can produce more accurate and stable predictions. And better predictions can be better for business.

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Analytics Vidhya

SEPTEMBER 9, 2019

Overview Here’s a unique data science challenge we don’t come across often – a marketing analytics hackathon! We bring you the top 3 inspiring. The post WNS Analytics Wizard 2019: Top 3 Winners’ Solutions from our Biggest Data Science Hackathon appeared first on Analytics Vidhya.

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DataRobot

SEPTEMBER 11, 2019

It is well-known that the AI revolution is transforming industries and businesses around the world. In this AI Simplified video, we define supervised machine learning and share some ways the military leverages this technology to maintain safety and ensure preparedness.

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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

SEPTEMBER 12, 2019

Artificial intelligence is coming to our homes. A growing number of people use smart devices that are developed with state-of-the-art AI technology. The market for smart homes is going to rise as new AI advances bring big changes to the industry. One survey from last year found that only 12-16% of homes in the United States are equipped with smart devices.

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KDnuggets

SEPTEMBER 10, 2019

How does the scikit-learn machine learning library for Python compare to the mlr package for R? Following along with a machine learning workflow through each approach, and see if you can gain a competitive advantage by knowing both frameworks.

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DataRobot Blog

SEPTEMBER 11, 2019

Financial Planning and Analysis (FP&A) business professionals are responsible for mapping out a company’s financial future. They transform company goals into actionable plans by analyzing the current state of financial management affairs, then take the time to create a roadmap plan that details how to reach the destination. . Creating those plans require ingesting massive amounts of data resources, aggregating, cleansing, and standardizing that data, and then performing analysis on the finis

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KDnuggets

SEPTEMBER 12, 2019

There is no such thing as a free lunch in life or data science. Here, we'll explore some science philosophy and discuss the No Free Lunch theorems to find out what they mean for the field of data science.

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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.

Data Science

KDnuggets

SEPTEMBER 10, 2019

In this post, I am going to be talking about some of the most important graph algorithms you should know and how to implement them using Python.

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KDnuggets

SEPTEMBER 9, 2019

In this blog, Seth DeLand of MathWorks discusses two of the most common obstacles relate to choosing the right classification model and eliminating data overfitting.

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KDnuggets

SEPTEMBER 9, 2019

BERT is changing the NLP landscape and making chatbots much smarter by enabling computers to better understand speech and respond intelligently in real-time.

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KDnuggets

SEPTEMBER 13, 2019

This post expands on the NAACL 2019 tutorial on Transfer Learning in NLP organized by Matthew Peters, Swabha Swayamdipta, Thomas Wolf, and Sebastian Ruder. This post highlights key insights and takeaways and provides updates based on recent work.

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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.

Analytics

KDnuggets

SEPTEMBER 11, 2019

Online hate speech is a complex subject. Follow this demonstration using state-of-the-art graph neural network models to detect hateful users based on their activities on the Twitter social network.

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KDnuggets

SEPTEMBER 9, 2019

I am really interested in creating a tight, clean pipeline for disaster relief applications, where we can use something like crowd sourced building polygons from OSM to train a supervised object detector to discover buildings in an unmapped location.

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KDnuggets

SEPTEMBER 9, 2019

In this article, we’ll look at research and model architectures that have been written and developed to do just that using deep learning.

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KDnuggets

SEPTEMBER 12, 2019

It turned out that, if we ask the weak algorithm to create a whole bunch of classifiers (all weak for definition), and then combine them all, what may figure out is a stronger classifier.

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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.

Analytics

KDnuggets

SEPTEMBER 9, 2019

Recently, Alphabet’s subsidiaries Waymo and DeepMind partnered to find a more efficient process to train self-driving vehicles algorithms and their work took them back to one of the cornerstones of our history as species: evolution.

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KDnuggets

SEPTEMBER 10, 2019

ODSC has developed a mini-bootcamp, designed to reduce the time and monetary costs of discovering which pathway into data science you should take. In this article, we’ll discuss seven reasons why ODSC’s Mini-Bootcamp might be right for you.

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KDnuggets

SEPTEMBER 11, 2019

Data Driven Government is coming to Washington, DC, Sep 26, and includes a stellar lineup of experts who will share the emerging trends and best practices of government agencies in the current use of data analytics to enhance mission outcomes. Use code KDNUGGETS to get 15% off.

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KDnuggets

SEPTEMBER 13, 2019

I am a Git god, why do I need another version control system for Machine Learning Projects?

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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.