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How to tackle lack of data: an overview on transfer learning

Data Science Blog

Presumably due to this fact, Andrew Ng, in his presentation in NeurIPS 2016, gave a rough and abstract predictions of how transfer learning in machine learning would make commercial success like white lines in the figure below. And sometimes ad hoc analysis with simple data visualization will help your decision makings.

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Announcing the Winners of ‘The NFL Fantasy Football’ Data Challenge

Ocean Protocol

Fantasy Football is a popular pastime for a large amount of the world, we gathered data around the past 6 seasons of player performance data to see what our community of data scientists could create. This report took the data set provided in the challenge, as well as external data feeds and alternative sources.

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New projects contribute to digital commons

Hacker News

By addressing these important gaps in timing-aware design and incremental formal verification, the project aims to contribute important technological bricks to the open-source community, supporting the development of more capable and reliable open source EDA tools. Basic scripting commands compatible with Nutmeg will be provided.

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Multivariate Time Series Forecasting

Mlearning.ai

I used the Plotly library as a visualization tool to gain insights from my dataset. Plotly proved to be quite helpful in creating interactive graphs for visualizing the data. I recommend using this library for data visualization purposes. The residuals show the deviation levels around the data.