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Top 25 Machine Learning Startups To Watch In 2020

One in ten enterprises now uses ten or more AI applications, with leading use cases being chatbots, process optimization, and fraud analysis, according to MMC Ventures. Open jobs requiring TensorFlow experience is a useful way to quantify how prevalent machine learning is becoming in business today. There are 3,602 open positions in the U.S. on LinkedIn that require TensorFlow expertise and 10,345 open positions worldwide as of today. Open jobs on LinkedIn requesting machine learning expertise in the U.S. further reflect its growing dominance in all businesses. There are 37,492 jobs in the U.S. today, according to LinkedIn, that list machine learning as a required skill, and 81,385 worldwide. Please see the latest roundup of machine learning forecasts and market estimates, 2020, for more market data on machine learnings' exponential growth.
Guest PostJune 27th 20221 min read
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One in ten enterprises now uses ten or more AI applications, with leading use cases being chatbots, process optimization, and fraud analysis, according to MMC Ventures. Open jobs requiring TensorFlow experience is a useful way to quantify how prevalent machine learning is becoming in business today. There are 3,602 open positions in the U.S. on LinkedIn that require TensorFlow expertise and10,345 open positions worldwide as of today. Open jobs on LinkedIn requesting machine learning expertise in the U.S. further reflect its growing dominance in all businesses. There are 37,492 jobs in the U.S. today, according to LinkedIn, that list machine learning as a required skill, and 81,385 worldwide. Please see the latest roundup of machine learning forecasts and market estimates, 2020, for more market data on machine learnings' exponential growth.

  • Rosetta.ai – Rosetta.ai helps e-commerce businesses increase conversion and increase order value with deep learning-based technology to analyze the individual consumer's preferences and behaviors, predict future sales, and provide personalized recommendations for online and offline during the consumer's shopping journey. Different vertical e-commerce markets have different shopping behaviors and preferences. Rosetta.ai focuses on the vertical e-commerce industry, the fashion industry, and dives more into the fashion, e.g., apparel, cosmetics, and accessory, etc., to build the dedicated deep learning models and algorithms for it and automatically arrange suitable models and algorithms for e-commerce. Rosetta.ai has raised two rounds. Their latest funding was raised on Mar 10, 2020, from a Convertible Note round.

Source: forbes.com

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