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🤔 Big Data or ML? What should I choose?

A month ago, there was a fork in the road for students of the Big Data / Machine Learning Engineer (BDMLE) course: should they immerse themselves more in Big Data (BD) or Machine Learning (ML)?

We conferred and decided to share with you a litmus test and information on the technology stack. Hopefully, this knowledge will simplify your choice ahead of the new Tech Orda round.

Litmus test: if you like programming more than deducing formulas and counting integrals, then Big Data is more suitable for you. Otherwise, ML.


Big Data: HDFS, Hadoop, Hive, Spark, Kafka + Spark Structured Streaming, NoSQL (Cassandra), Data Layout (Parquet, ORC, compression), Hadoop 3+ buns.

Machine Learning (basic): numpy, scipy, pandas, sklearn, pytorch, xgboost / lightgbm / catboost.

What would you choose?

🐳 Big Data

⚡️ Machine Learning

Write the answers in the comments

❤️ BD + ML, shake, but do not mix

photo: Artyom

#work #study

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