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5 Apache Spark Best Practices

July 4, 2022/0 Comments/in Big Data, Data Science Hack, Tool Introduction, Tools /by Sai Priya

Already familiar with the term big data, right? Despite the fact that we would all discuss Big Data, it takes a very long time before you confront it in your career. Apache Spark is a Big Data tool that aims to handle large datasets in a parallel and distributed manner. Apache Spark began as a research project at UC Berkeley’s AMPLab, a student, researcher, and faculty collaboration centered on data-intensive application domains, in 2009.

Stop saying “trial and errors” for now: seeing reinforcement learning through some spectrums

July 1, 2022/0 Comments/in Artificial Intelligence, Data Science, Deep Learning /by Yasuto Tamura

Some of you might have got away with explaining reinforcement learning (RL) only by saying an obscure thing like “RL enables computers to learn through trial and errors.” But if you have patiently read my articles so far, you might have come to say “RL is a family of algorithms which simulate procedures similar to dynamic programming (DP).”

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3 Types of Preventative Maintenance for Data Centers

June 28, 2022/0 Comments/in Predictive Analytics /by Shannon Flynn

Image Source: source unsplash.com Downtime for a data center can be extraordinarily costly — potentially leading to lost revenue, lost customers and a damaged reputation. Preventative maintenance (PM) helps keep essential data center equipment running for as long as possible (while also making potential issues easier to spot). However, there are many strategies for preventative […]

It’s All About Data: The Training of AI Models

June 20, 2022/0 Comments/in Artificial Intelligence, Data Science, Deep Learning, Machine Learning, Main Category /by Benjamin Aunkofer

In deep learning, there are different training methods. Which one we use in an AI project depends on the data provided by our customer: how much data is there, is it labeled or unlabeled? Or is there both labeled and unlabeled data?

Automatic Financial Trading Agent for Low-risk Portfolio Management using Deep Reinforcement Learning

June 9, 2022/0 Comments/in Artificial Intelligence, Data Science, Deep Learning, Machine Learning, Main Category /by Jieyun Hu

This article focuses on autonomous trading agent to solve the capital market portfolio management problem. Researchers aim to achieve higher portfolio return while preferring lower-risk actions. It uses deep reinforcement learning Deep Q-Network (DQN) to train the agent.