BigData News Wednesday, April 4 Scikit flow, Deep learning, Learn data analytics & more…
BigData News TLDR / Table of Contents
- Scikit Flow: Easy Deep Learning with TensorFlow and Scikit-learn
- Scikit Flow, deep learning, deep learning library, neural networks, TensorFlow
- Weekly Digest, April 2
- Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture o…
- Learn data analytics, online Business Analytics, Wharton Customer Analytics, Learn data analysis, high level rigor
- These 100 companies are leading the world in artificial intelligence
- CB Insights has released its list of the 100 companies leading the way in AI.
- firm CB Insights, promising A.I. startups, World Economic Forum, gargantuan opportunity, global GDP
- It is, of course, difficult to estimate true adoption rates, but TensorFlow’s Github repository has nearly twice the number of stars of both the next most-starred machine learning project, Scikit-learn, and closest deep learning project, Berkeley Vision and Learning Center’s Caffe.
- Technically, TensorFlow is an open source software library for numerical computation using data flow graphs, and while it is (predominantly) used for machine learning and deep learning research (and production), the system is general enough so that it is applicable to a wide array of additional domains.
- And now back to Scikit Flow (skflow): Since (almost) everyone in the Python machine learning ecosystem has some knowledge of Scikit-learn, what if you could immediately harness the modelling power of TensorFlow by channelling the syntactical brevity of Scikit-learn?
- Scikit Flow (the very name name alone alludes to this harnessing and channelling) is officially billed as follows: – – Practically, and more explicitly, Scikit Flow is a high level wrapper for the TensorFlow deep learning library, which allows the training and fitting of neural networks using the brief, familiar…
- Scikit Flow also has a stock recurrent neural network, some additional classifiers, and as an early work and one of the official TensorFlow projects, one could assume additional stock architectures and classifiers will soon be added.
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- Whether you fear it or embrace it, the A.I. revolution is comingand it promises to have an enormous impact on the world economy.
- To identify which private companies are set to make the most of it, research firm CB Insights recently released its 2018 A.I. 100, a list of the most promising A.I. startups globally (grouped by sector in the graphic above).
- They were chosen, from a pool of over 1,000 candidates, by CB Insights Mosaic algorithm, based on factors like investor quality and momentum.
- Chinas Bytedance leads in funding with $3.1 billion, but 76 of the 100 startups are U.S.-based.
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