How to Create a Great User Experience: Fresh App Personalization Ideas

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Have you ever made a purchase online following someone’s advice? What about the recommendations that were prompted to you by the website itself? Being quite a common element of an eCommerce app, tailored product recommendations have proven to be an extremely effective tool for revenue growth.

Namely, Amazon’s recommendation engine is said to generate 35% of the platform’s total revenue. Taking into account its actual sales volume ($178 billion in 2017), this makes an additional $62 billion per year. Quite impressive, right?

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Machine Learning in the World of Nuclear Physics [Video]

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How does TensorFlow apply to nuclear physics? In this video, I chat with Ian Langmore to learn about power generated from nuclear fusion, new plasma generator machines, and how TensorFlow is helping with plasma measurement.

To learn more about what we talked about:


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Accelerate: Building and Scaling High-Performing Technology Organizations [Review]

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Nicole Forsgren’s, Jez Humble’s, and Gene Kim’s latest book, Accelerate: Building and Scaling High Performing Technology Organizations, describes the factors that drive high-performing tech organizations, derived from the data that has been aggregated with the State of DevOps Report since 2014.

Accelerate: Building and Scaling High-Performing Technology Organizations

Accelerateis a must-read book for anyone involved in building Agile organizations and teams. It lays out a path to success based on a statistical analysis of data. It also puts an end to the popular narrative that "becoming Agile" is somehow a fuzzy process. The data shows that there are patterns at all levels that successful Agile organizations share.

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What Enterprise Software Delivery Can Learn From a Woman, Hackathon, and ML

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What a special experience. An old friend and colleague, Lynn Pausic, one of the co-founders of Expero — a company with extensive experience in Machine Learning applied to complex business and technical problems — asked if I would help judge a “Machine Learning hackathon for women.” How could I say no to that?

Eight teams of women presented highly innovative and varied ideas for Machine Learning that could be applied to do good in the world, help improve and save lives, and even make home-cooking easier!


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Using AI And ML For Translation Solutions

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Natural Language Processing; it’s Artificial Intelligence that learns words and patterns of words so that it can respond to human searches and questions. Siri and Alexa are examples of this technology.

And this technology is continually improving. As more and more conversations are held with these machines, they continue to learn and respond more accurately.


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Technical Debt and Supporting Prior Decisions

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Recently, I was asked to attend a session at a large corporation. The room was filled with technology-based executives, development managers, and enterprise architects. Also in attendance were a few of my peers from 

Upon leaving this discussion, I found myself wondering just how many other corporations are facing this same dilemma.

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5 Easy Hacks To Quickly Learn Any Programming Language

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In today’s society, everything we do has some form of software programming involved. Whether it’s navigating through the various applications we have on our phone, browsing our favorite websites during downtime, or inputting critical data into a software at work – programming surrounds our daily interactions. As companies increasingly look for ways to cut cost and increase revenue, programmers are needed to drive this innovation and propel society into the future.

The demand for programmers is not only making the job one of the most lucrative but also one of the fastest growing over the decade – 24% projected growth over the next decade according to the Bureau of Labor Statistics.

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Python vs. R: Which Should You Choose For Your Next ML Project?

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Data science is all about capturing data in an insightful way, whereas Machine Learning is a key area of it. Data science is a fantastic blend of advanced statistics, problem-solving, mathematics expertise, data inference, business acumen, algorithm development, and real-world programming ability. And Machine Learning is a set of algorithms that enable software applications to become more precise in predicting outcomes or take actions to separate it without being explicitly programmed.

The distinction between data science and Machine Learning is a bit fluid, but the main idea is that data science emphasizes statistical inference and interpretability, while Machine Learning prioritizes predictive accuracy over model interpretability. And for both data science and Machine Learning, open source has become almost the de facto license for innovative new tools.


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Be an Amazing Programmer With These 5 Easy Tips

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Computer programming is the process of writing and designing instructions to build an executable computer program for accomplishing a specific computing task. It involves tasks such as analysis, flow-charting, generating algorithms, and resource consumption. It is then implemented by choosing a programming language which the computer understands, which in technical terms is called “source code”. The process of programming requires expertise on various fronts that include; knowledge of the application domain, specialized algorithms, and formal logic. The tasks related to programming include:

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Executive Insights on the Current and Future State of Artificial Intelligence

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This article is featured in the new DZone Guide to Artificial Intelligence: Automating Decision-Making. Get your free copy for more insightful articles, industry statistics, and more!

To gather insights on the state of artificial intelligence (AI), and all of its subsegments — machine learning (ML), natural language processing (NLP), deep learning (DL), robotic process automation (RPA), regression, etc., we talked to 21 executives who are implementing AI in their own organization and helping others understand how AI can help their business. Specifically, we spoke to:


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