AI News Tuesday, March 13 Logistic regression, Linear regression, Built-in ai chip & more…
AI News TLDR / Table of Contents
- Machine Learning Algorithms: Which One to Choose for Your Problem
- logistic regression, linear regression, algorithms, neural networks, features
- AI smartphones will soon be standard, thanks to machine learning chip
- ARM made the chip in nearly every smartphone. Now, they’re working on a chip that brings machine learning to your mobile, making AI smartphones ubiquitous.
- built-in AI chip, British chip design, Chinese smartphone maker, AI smartphones, AI software
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- This article will try to explain basic concepts and give some intuition of using different kinds of machine learning algorithms in different tasks.
- In this article forStatsbot, I will try to explain basic concepts and give some intuition of using different kinds of machine learning algorithms in different tasks.
- Your goal is to find the most optimal weights w1,…wn and bias for these features according to some loss function, for example,MSEorMAEfor a regression problem.
- More complex algorithms suffer from overfitting many features and not huge datasets, while linear regression provides decent quality.
- Neural Networksare a new era of machine learning algorithms and can be applied for many tasks, but their training needs huge computational complexity.
- Almost every major player in the smartphone industry now says that their devices use the power of artificial intelligence (AI), or more specifically, machine learning algorithms.
- That might soon change: thanks to a processor dedicated to machine learning for mobile phones and other smart-home devices, AI smartphones could one day be standard.
- British chip design firm ARM, the company behind virtually every chip in todays smartphones, now wants to put the power of AI into every mobile device.
- Their built-in AI chip would allow devices to continue running machine learning algorithms even when offline.
- We analyze compute workloads, work out which bits are taking the time and the power, and look to see if we can improve on our existing processors, Jem Davies, ARMs machine learning group head, told the MIT Technology Review.
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