Curated essays about the future of Data Science. Production Data Science and learning resources for continuous learning. Covers Data Science, Data Engineering, MLOps & DataOps. Curated by people at https://nibble.ai/
Hi! This week we’ve got a mix of learning and doing. We’d love to hear your feedback on this issue, feel free to share with us.
The whole picture, in layman’s terms, supported by very cool illustrations. Recommended even if you’re already familiar with Machine Learning. If not, it’s mandatory reading. #article #machinelearning #beginner
Simple but powerful, the K-Nearest Neighbors can work very well on low-dimensional datasets or datasets gone through dimensionality reduction techniques. This in-depth tutorial will guide you through the intuition and mathematical details of the algorithm.
Docker can be very useful when doing data science work, but it’s not easy to get started with it. This article is the first part of a series on Docker and focuses on explaining what Docker is and why it is useful.