Opinions, Interviews, Reports
We welcome guest blogs and opinions - see submission guidelines.
Latest:
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What Do Data Scientists in Europe Do & How Much Are They Worth? - Jan 23, 2020.
Interested in knowing what a data scientist is worth in Europe, and what one does? Read this overview of a recent survey on the topic and gain some insight into the European data science professional job market. -
Top 5 AI trends for 2020 - Jan 21, 2020.
We are all witnessing a staggering growth of AI technology with so many new benefits for people while also changing the way we live and work. As AI continues to grow, which applications will have a significant impact in 2020? -
Artificial Intelligence Books to Read in 2020 - Jan 21, 2020.
Here are some AI-related books that I’ve read and recommend for you to add to your 2020 reading list! -
I wanna be a data scientist, but… how? - Jan 20, 2020.
It’s easy to say "I wanna be a data scientist," but... where do you start? How much time is needed to be desired by companies? Do you need a Master’s degree? Do you need to know every mathematical concept ever derived? The journey might be long, but follow this plan to help you keep moving forward toward your career goal. -
The Future of Machine Learning - Jan 17, 2020.
This summary overviews the keynote at TensorFlow World by Jeff Dean, Head of AI at Google, that considered the advancements of computer vision and language models and predicted the direction machine learning model building should follow for the future. -
Top 9 Mobile Apps for Learning and Practicing Data Science - Jan 17, 2020.
This article will tell you about the top 9 mobile apps that help the user in learning and practicing data science and hence is improving their productivity. -
Top 10 Technology Trends for 2020 - Jan 16, 2020.
With integrations of multiple emerging technologies just in the past year, AI development continues at a fast pace. Following the blueprint of science and technology advancements in 2019, we predict 10 trends we expect to see in 2020 and beyond. -
Schema Evolution in Data Lakes - Jan 16, 2020.
Whereas a data warehouse will need rigid data modeling and definitions, a data lake can store different types and shapes of data. In a data lake, the schema of the data can be inferred when it’s read, providing the aforementioned flexibility. However, this flexibility is a double-edged sword. -
7 AI Use Cases Transforming Live Sports Production and Distribution - Jan 14, 2020.
Here are 7 powerful AI led use cases both for linear television and for OTT apps that are transforming the live sports production landscape. -
Graph Machine Learning Meets UX: An uncharted love affair - Jan 13, 2020.
When machine learning tools are developed by technology first, they risk failing to deliver on what users actually need. It can also be difficult for development teams to establish meaningful direction. This article explores the challenges of designing an interface that enables users to visualise and interact with insights from graph machine learning, and explores the very new, uncharted relationship between machine learning and UX. -
Applying Occam’s razor to Deep Learning - Jan 10, 2020.
Finding a deep learning model to perform well is an exciting feat. But, might there be other -- less complex -- models that perform just as well for your application? A simple complexity measure based on the statistical physics concept of Cascading Periodic Spectral Ergodicity (cPSE) can help us be computationally efficient by considering the least complex during model selection. -
Deepfakes Security Risks - Jan 10, 2020.
Deepfakes have instilled panic in experts since they first emerged in 2017. Microsoft and Facebook have recently announced a contest to identify deepfakes more efficiently. -
7 Steps to a Job-winning Data Science Resume - Jan 10, 2020.
A resume plays a key role in bagging that dream data science job. We break down the nuances of a job-winning data science resume so that you can go ahead and transform your own resume. -
7 Resources to Becoming a Data Engineer - Jan 7, 2020.
An estimated 8,650% growth of the volume of Data to 175 zetabytes from 2010 to 2025 has created an enormous need for Data Engineers to build an organization's big data platform to be fast, efficient and scalable. -
5 Ways AI Is Changing The Healthcare Industry - Jan 7, 2020.
The healthcare AI market is expected to reach 28 billion dollars by the year 2025. With such exponential growth, AI is undoubtedly likely to bring some drastic changes in the healthcare industry. Let’s look at five ways of how AI has changed the healthcare industry. -
Cartoon: Teaching Ethics to AI - Jan 4, 2020.
Ethics in AI has received significant attention recently, and the new KDnuggets cartoon examines the problem of teaching ethics to artificially intelligent entities. -
Why Python is One of the Most Preferred Languages for Data Science? - Jan 3, 2020.
Why do most data scientists love Python? Learn more about how so many well-developed Python packages can help you accomplish your crucial data science tasks. -
How HR Is Using Data Science and Analytics to Close the Gender Gap - Jan 3, 2020.
The gender gap can extend to the lack of equal representation in certain industries or career paths, and there's an extraordinarily long way to go before people will be on equal footing in the labor market. Human resources professionals can rely on data analytics to make progress. -
Accuracy vs Speed – what Data Scientists can learn from Search - Jan 2, 2020.
Delivering accurate insights is the core function of any data scientist. Navigating the development road toward this goal can sometimes be tricky, especially when cross-collaboration is required, and these lessons learned from building a search application will help you negotiate the demands between accuracy and speed. -
Automated Machine Learning: How do teams work together on an AutoML project? - Jan 2, 2020.
In this use case, available to the public on GitHub, we’ll see how a data scientist, project manager, and business lead at a retail grocer can leverage automated machine learning and Azure Machine Learning service to reduce product overstock.
December:
- What is the most important question for Data Science (and Digital Transformation)
- Towards a Quantitative Measure of Intelligence: Breaking Down One of the Most Important AI Papers of 2019, Part II
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How To “Ultralearn” Data Science: summary, for those in a hurry
For those of you in a hurry and interested in ultralearning (which should be all of you), this recap reviews the approach and summarizes its key elements -- focus, optimization, and deep understanding with experimentation -- geared toward learning Data Science. - Towards a Quantitative Measure of Intelligence: Breaking Down One of the Most Important AI Papers of 2019, Part I
- How To “Ultralearn” Data Science: deep understanding and experimentation, Part 4
- KDnuggets Cartoon in an English textbook?
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What is a Data Scientist Worth?
What is the Salary of a Data Scientist in 2019? Let's have a look at some data to see how we can answer that question. - How To “Ultralearn” Data Science: optimization learning, Part 3
- 5 Ways to Apply Ethics to AI
- The 4 fastest ways NOT to get hired as a data scientist
- Automatic Text Summarization in a Nutshell
- The ravages of concept drift in stream learning applications and how to deal with it
- How To “Ultralearn” Data Science: removing distractions and finding focus, Part 2
- Industry AI, Analytics, Machine Learning, Data Science Predictions for 2020
- Microsoft Introduces Icebreaker to Address the Famous Ice-Start Challenge in Machine Learning
- Xavier Amatriain’s Machine Learning and Artificial Intelligence 2019 Year-end Roundup
- KDnuggets Poll: How well do current AutoML solutions work?
- How To “Ultralearn” Data Science, Part 1
- Dusting Under the Bed: Machine Learners’ Responsibility for the Future of Our Society
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AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020
We asked leading experts - what are the most important developments of 2019 and 2020 key trends in AI, Analytics, Machine Learning, Data Science, and Deep Learning? This blog focuses mainly on technology and deployment. - NeurIPS 2019 Outstanding Paper Awards
- Scalable graph machine learning: a mountain we can climb?
- Moving Predictive Maintenance from Theory to Practice
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The 4 Hottest Trends in Data Science for 2020
The field of Data Science is growing with new capabilities and reach into every industry. With digital transformations occurring in organizations around the world, 2019 included trends of more companies leveraging more data to make better decisions. Check out these next trends in Data Science expected to take off in 2020.
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AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020
As we say goodbye to one year and look forward to another, KDnuggets has once again solicited opinions from numerous research & technology experts as to the most important developments of 2019 and their 2020 key trend predictions.
- DeepMind Unveils MuZero, a New Agent that Mastered Chess, Shogi, Atari and Go Without Knowing the Rules
- Accuracy Fallacy: The Media’s Coverage of AI Is Bogus
- Why software engineering processes and tools don’t work for machine learning
- The Essential Toolbox for Data Cleaning
- Artificial Friend or Virtual Foe
- Explainability: Cracking open the black box, Part 1
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A Non-Technical Reading List for Data Science
The world still cannot be reduced to numbers on a page because human beings are still the ones making all the decisions. So, the best data scientists understand the numbers and the people. Check out these great data science books that will make you a better data scientist without delving into the technical details.
- Top 7 Data Science Use Cases in Trust and Security
- Google Open Sources MobileNetV3 with New Ideas to Improve Mobile Computer Vision Models
