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How the semiconductor industry is leveraging high-performance computing to drive innovation

IBM Journey to AI blog

As semiconductor manufacturers strive to keep up with customer expectations, electronic design automation (EDA) tools are the keys to unlocking the solution. However, to truly drive innovation at scale, EDA leaders need massive computing power. Cadence leverages IBM Cloud HPC Cadence is a global leader in EDA.

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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. “Shut up and annotate!” ” could be often the best practice in practice.

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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 method was chosen to rigorously assess and fine-tune each model’s performance using a comprehensive range of hyperparameters.

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Unveiling Market Dynamics: Winners of the Google Trends Analysis and Predictive Modeling

Ocean Protocol

Essential tasks included conducting exploratory data analyses (EDA), identifying correlations, and investigating how historical and current trends could forecast future market movements. Data scientists across various expertise levels engaged in this challenge to determine Google Trends’ impact on cryptocurrency valuations.

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Multivariate Time Series Forecasting

Mlearning.ai

I finished to EDA & Time Series Analysis, I will build some ML or DL model. In addition, I aim to reveal valuable patterns and trends in the data set by examining the statistical properties of numerical variables. Finally, the Residuals graph shows the residuals. The residuals show the deviation levels around the data.