KDnuggets

NOVEMBER 5, 2019

Artificial Intelligence continues to fill the media headlines while scientists and engineers rapidly expand its capabilities and applications. With such explosive growth in the field, there is a great deal to learn. Dive into these 10 free books that are must-reads to support your AI study and work.

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Analytics Vidhya

NOVEMBER 3, 2019

Overview Here are six open-source data science projects to enhance your skillset These projects cover a diverse set of domains, from computer vision to. The post 6 Exciting Open Source Data Science Projects you Should Start Working on Today appeared first on Analytics Vidhya.

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Dataconomy

NOVEMBER 4, 2019

By leveraging Data Science, AI, and other digital technologies, the healthcare industry could build complementary health solutions that are personalized to the specific needs of patients. Here is how and why. The world population grows by more than 80 million per year, according to a 2017 report by the United Nations. The post Transforming Patient Health: The Power of Data Science in Pharmaceuticals appeared first on Dataconomy.

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Data Science 101

NOVEMBER 7, 2019

Microsoft just held one of its largest conferences of the year, and a few major announcements were made which pertain to the cloud data science world. Here they are in my order of importance (based upon my opinion). Azure Synapse. I think this announcement will have a very large and immediate impact. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake.

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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?

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KDnuggets

NOVEMBER 7, 2019

This post will walkthrough a Python implementation of a vocabulary class for storing processed text data and related metadata in a manner useful for subsequently performing NLP tasks.

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Analytics Vidhya

NOVEMBER 5, 2019

Overview Extracting features from tabular or image data is a well-known concept – but what about graph data? Learn how to extract features from. The post Learn How to Perform Feature Extraction from Graphs using DeepWalk appeared first on Analytics Vidhya.

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Smart Data Collective

NOVEMBER 6, 2019

Smart cities are gaining popularity across the world thanks to the convenience and efficiency they bring to citizens, visitors, and government leadership. Smart city technology can use data to revolutionize what it means to live and work in a city. First, however, we need the right kind of storage solutions to make all these proposed features functional.

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KDnuggets

NOVEMBER 4, 2019

Customer Segmentation can be a powerful means to identify unsatisfied customer needs. This technique can be used by companies to outperform the competition by developing uniquely appealing products and services.

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Analytics Vidhya

NOVEMBER 6, 2019

Overview Deep learning is a vast field but there are a few common challenges most of us face when building models Here, we talk. The post 4 Proven Tricks to Improve your Deep Learning Model’s Performance appeared first on Analytics Vidhya.

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Explosion

NOVEMBER 8, 2019

“Artificial intelligence” is everywhere in the headlines. Many futuristic-sounding things suddenly seem possible. It’s not easy to judge what all these technological advances mean. What is hype and what really works? And how should we imagine the future?

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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.

Database

Smart Data Collective

NOVEMBER 7, 2019

Big data is playing a very important role in the future of branding. Last year, Samantha Bhargav wrote a great article on ways big data can help with branding strategies. There are a number of benefits, as Bhargav points out. One of the biggest is customer-centric marketing. Ways that Big Data Promotes Stronger Branding Practices. Whether you are a brand that has just started off or a brand that has become a dominant force over the years, the same core principles are going to determine whether y

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KDnuggets

NOVEMBER 4, 2019

Check out this step-by-step walk through of some of the more confusing aspects of neural nets to guide you to making smart decisions about your neural network architecture.

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Analytics Vidhya

NOVEMBER 4, 2019

Data engineers are a rare breed. Without them, a machine learning project would crumble before it starts. Their knowledge and understanding of software and. The post Master Data Engineering with these 6 Sessions at DataHack Summit 2019 appeared first on Analytics Vidhya.

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Victor Zhou

NOVEMBER 8, 2019

EDIT: We did it - Sendy has released a patch (v4.0.3.3) for this issue! I recommend upgrading if you’re affected. Thanks to Sendy for the quick response to this blog post, and thanks to every reader who helped make this happen. A few months ago, I switched from Mailchimp to Sendy , a self-hosted email newsletter alternative. I wrote a whole post about why I switched from Mailchimp to Sendy , but the gist is that Mailchimp got too expensive too fast.

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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

NOVEMBER 7, 2019

ISPs are using data analytics in a variety of ways. Many consumers may be concerned about this, because they are known to exploit customer data. However, they use data in a number of benevolent ways, which many people will be okay with. Pew Research has shown most customers are okay with companies collecting their data if it is used for holistic purposes.

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KDnuggets

NOVEMBER 7, 2019

In this tutorial, we show how to apply mathematical set operations (union, intersection, and difference) to Pandas DataFrames with the goal of easing the task of comparing the rows of two datasets.

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DataCentric podcast

NOVEMBER 7, 2019

NetApp is about more than just about on-prem enterprise storage. They are changing with the industry as it embraces HCI, Cloud Native, and Kubernetes as part of the Data Fabric. This is critical to the company's strategy. We had the chance to sit separately with NetApp's SVP & GM of Cloud Native (which includes its Kubernetes/Containers activity) Anthony Lye to talk about how NetApp and its enterprise customers view that space, as well as how they are evolving from an "on-prem fi

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DataRobot

NOVEMBER 8, 2019

Back when I was doing my undergraduate degree, I remember being asked to proofread a friend’s economics essay. I didn’t make it past the first paragraph before spotting the surprising phrase “John Maynard Keynes' work was impotent.” While there was a possibility that my friend wanted to criticize Keynes’ work, the remainder of the essay was pro-Keynes.

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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

Smart Data Collective

NOVEMBER 6, 2019

Big data and cannabis are two seemingly different concepts. However, the two industries tie in very well with each other. CBD companies are relying more on big data than ever before. In June, Nicole Martin wrote a very detailed article for Forbes on the role of big data in operations management for the cannabis industry. “Data helps to drive every industry now.

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KDnuggets

NOVEMBER 4, 2019

The new release of PyTorch includes some impressive open source projects for deep learning researchers and developers.

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KDnuggets

NOVEMBER 8, 2019

A boxplot. It can tell you about your outliers and what their values are. It can also tell you if your data is symmetrical, how tightly your data is grouped, and if and how your data is skewed.

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KDnuggets

NOVEMBER 7, 2019

Careful preprocessing of data for your machine learning project is crucial. This overview describes the process of data cleaning and dealing with noise and missing data.

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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

NOVEMBER 8, 2019

Do you want to extract csv files with Python and visualize them in R? How does preparing everything in R and make conclusions with Python sound? Both are possible if you know the right libraries and techniques. Here, we’ll walk through a use-case using both languages in one analysis.

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KDnuggets

NOVEMBER 8, 2019

Data Natives is an outstanding conference that lets you meet many talented Data Scientists and Data Professionals. Find your dream company or your dream employee and level up for 2020. Use code DN19_KDNuggets_50 to save.

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KDnuggets

NOVEMBER 6, 2019

My short answer is this: Yes, another AI Winter will be here if you don’t deploy more ML solutions. You and your Data Science teams are the last line of defense against the AI Winter. You need to solve five key challenges to keep the momentum up.

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KDnuggets

NOVEMBER 6, 2019

This guide explores research centered on a variety of advanced loss functions for machine learning models.

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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

NOVEMBER 5, 2019

The maths behind Bayes will be better understood if we first cover the theory and maths underlying another fundamental method of probabilistic machine learning: Maximum Likelihood. This post will be dedicated to explaining it.

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KDnuggets

NOVEMBER 8, 2019

Data Science is pitched as a modern and exciting job offering high satisfaction. Does its reality really live up to the hype? Here, we show what it's really like to work as a Data Scientist.

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KDnuggets

NOVEMBER 6, 2019

Learn about statistical fallacies Data Scientists should avoid; New and quite amazing Deep Learning capabilities FB has been quietly open-sourcing; Top Machine Learning tools for Developers; How to build a Neural Network from scratch and more.

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KDnuggets

NOVEMBER 6, 2019

Follow these eight headings of an audit sheet that business analysts should address before submitting the results of their analytics project. One recommended approach is to rewrite each step as a question, answer it, and then attach it to your project.

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Analytics Analytics 121

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.