Sat.Apr 15, 2017 - Fri.Apr 21, 2017

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Intro to Machine Learning: 10 Essential Algorithms For Machine Learning Engineers

Dataconomy

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based. The post Intro to Machine Learning: 10 Essential Algorithms For Machine Learning Engineers appeared first on Dataconomy.

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Making a simple Raspberry Pi Bitcoin/Ethereum trading bot

Christian Haschek

[update] I have extended the bot to be able to trade *

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Banks and fintechs, instead of banks versus fintechs

Dataconomy

In 2016, global market uncertainty seemed to make investors somewhat more cautious, thanks to the results of the votes in the UK and the USA. However, fintech’s stellar run did not come to a halt. According to the February report by KPMG, venture capital investment in the space rose 7%, The post Banks and fintechs, instead of banks versus fintechs appeared first on Dataconomy.

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The History of Neural Networks

Dataconomy

Deep neural networks and Deep Learning are powerful and popular algorithms. And a lot of their success lays in the careful design of the neural network architecture. I wanted to revisit the history of neural network design in the last few years and in the context of Deep Learning. For. The post The History of Neural Networks appeared first on Dataconomy.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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Big Data 101: Intro To Probabilistic Data Structures

Dataconomy

Oftentimes while analyzing big data we have a need to make checks on pieces of data like number of items in the dataset, number of unique items, and their occurrence frequency. Hash tables or Hash sets are usually employed for this purpose. But when the dataset becomes so enormous that. The post Big Data 101: Intro To Probabilistic Data Structures appeared first on Dataconomy.

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