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AI Channels to Follow
AI is certainly playing an important role in our global fight against the novel coronavirus. These YouTube channels are recommended to keep you covered with the latest advancements in the field and how it is impacting our world.
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Coding habits for data scientists
While the core machine learning algorithms might only take up a few lines of code, it's the rest of your program that can get messy fast. Learn about some techniques for identifying bad coding habits in ML that add to complexity in code as well as start new habits that can help partition complexity.
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I Designed My Own Machine Learning and AI Degree
With so many pioneering online resources for open education, check out this organized collection of courses you can follow to become a well-rounded machine learning and AI engineer.
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Will Machine Learning Engineers Exist in 10 Years?
As can be common in many technical fields, the landscape of specialized roles is evolving quickly. With more people learning at least a little machine learning, this could eventually become a common skill set for every software engineer.
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Outbreak Analytics: Data Science Strategies for a Novel Problem
You walk down one aisle of the grocery store to get your favorite cereal. On the dairy aisle, someone sick from COVID-19 coughs. Did your decision to grab your cereal before your milk possibly keep you healthy? How can these unpredictable, near-random choices be included in complex models?
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Introducing Brain Simulator II: A New Platform for AGI Experimentation
A growing consensus of researchers contend that new algorithms are needed to transform narrow AI to AGI. Brain Simulator II is free software for new algorithm development targeted at AGI that you can experiment with and participate in its development.
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LSTM for time series prediction
Learn how to develop a LSTM neural network with PyTorch on trading data to predict future prices by mimicking actual values of the time series data.
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4 Realistic Career Options for Data Scientists
It’s almost 10 years since "Data Science" became mainstream. We ask less about how to get into Data Science, but wonder "what’s next?" This article includes insights on four non-trivial, but practical, options and their pitfalls.
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A Key Missing Part of the Machine Learning Stack
With many organizations having machine learning models running in production, some are discovering that inefficiencies exists in the first step of the process: feature definition and extraction. Robust feature management is now being realized as a key missing part of the ML stack, and improving it by applying standard software development practices is gaining attention.
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4 Steps to ensure your AI/Machine Learning system survives COVID-19
Many AI models rely on historical data to make predictions on future behavior. So, what happens when consumer behavior across the planet makes a 180 degree flip? Companies are quickly seeing less value from some AI systems as training data is no longer relevant when user behaviors and preferences change so drastically. Those who are flexible can make it through this crisis in data, and these four techniques will help you stay in front of the competition.
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