Remove the-good-and-the-bad-of-net-framework-programming
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15 Python Reinforcement Learning Project Ideas for Beginners

ProjectPro

Reinforcement Learning (or RL) is a branch of Machine Learning where an agent optimally learns to maximize the reward by interacting with the environment and understanding the consequences of good and bad actions. Reinforcement learning is the core of J.P. Reinforcement learning is the core of J.P.

Project 52
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How to Become a Data Engineer in 2024?

Knowledge Hut

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. According to reports by DICE Insights, the job of a Data Engineer is considered the top job in the technology industry in the third quarter of 2020.

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The Good and the Bad of Apache Kafka Streaming Platform

AltexSoft

After trying all options existing on the market — from messaging systems to ETL tools — in-house data engineers decided to design a totally new solution for metrics monitoring and user activity tracking which would handle billions of messages a day. We describe information search on the Internet with just one word — ‘google’. What is Kafka?

Kafka 93
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11 Ways To Stop Data Anomalies Dead In Their Tracks

Monte Carlo

A data anomaly is when the data is incorrect or missing as a result of bad data or broken data pipelines. That’s 549 engineering hours each month. Assuming an hour of a data engineer’s time costs roughly $75 that totals to nearly a half million dollars in engineering time a year spent on resolving data anomalies.

Food 52
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61 Data Observability Use Cases From Real Data Teams

Monte Carlo

Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. In less than three years it has gone from an idea sketched out in a Barr Moses blog post to climbing the Gartner Hype Cycle for Emerging Technology.

Data 52
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61 Data Observability Use Cases That Aren’t Totally Made Up

Monte Carlo

Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. In less than three years it has gone from an idea sketched out in a Barr Moses blog post to climbing the Gartner Hype Cycle for Emerging Technology.