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 Every Complex DataFrame Manipulation, Explained & Visualized Intuitively
Most Data Scientists might hail the power of Pandas for data preparation, but many may not be capable of leveraging all that power. Manipulating data frames can quickly become a complex task, so eight of these techniques within Pandas are presented with an explanation, visualization, code, and tricks to remember how to do it.
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Interpretability, Explainability, and Machine Learning – What Data Scientists Need to Know
The terms “interpretability,” “explainability” and “black box” are tossed about a lot in the context of machine learning, but what do they really mean, and why do they matter?
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When good data analyses fail to deliver the results you expect
To all those Data Scientists out there who thrive on discovering actionable insights from your data (all of you, right?), take heed from this cautionary tale of a data analysis, a dashboard, and a huge waste of resources.
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The Missing Teams For Data Scientists
Still today, too large a percent of data science projects fail, many of which can be attributed to the impacts of how hard missing data teams hit the data science team. Advocating for the missing data engineering and operations components to your team will make your professional life easier and more productive.
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Explaining the Explainable AI: A 2-Stage Approach
Understanding how to build AI models is one thing. Understanding why AI models provide the results they provide is another. Even more so, explaining any type of understanding of AI models to humans is yet another challenging layer that must be addressed if we are to develop a complete approach to Explainable AI.
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An Introduction to AI, updated
We provide an introduction to key concepts and methods in AI, covering Machine Learning and Deep Learning, with an updated extensive list that includes Narrow AI, Super Intelligence, and Classic Artificial Intelligence, as well as recent ideas of NeuroSymbolic AI, Neuroevolution, and Federated Learning.
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Getting A Data Science Job is Harder Than Ever – How to turn that to your advantage
Although many aspiring Data Scientists are finding it is becoming more difficult to land a job than it was in previous years, understanding what has changed in the hiring landscape can be used to to your advantage in matching with the best organization for your goals and interests.
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Software 2.0 takes shape
Software developers remain in very high demand as many organizations continue to experience workloads that far exceed available talent. AI-enhanced approaches that automate more areas of the software development lifecycle are in development with interesting potentials for how machine learning and natural language processing can significantly impact how software is designed, developed, tested, and deployed in the future.
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Behavior Analysis with Machine Learning and R: The free eBook
Check out this new free ebook to learn how to leverage the power of machine learning to analyze behavioral patterns from sensor data and electronic records using R.
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Deep Learning for Virtual Try On Clothes – Challenges and Opportunities
Learn about the experiments by MobiDev for transferring 2D clothing items onto the image of a person. As part of their efforts to bring AR and AI technologies into virtual fitting room development, they review the deep learning algorithms and architecture under development and the current state of results.
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Every Complex DataFrame Manipulation, Explained & Visualized Intuitively
An Introduction to AI, updated