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8 Ways to Optimize AWS Glue Jobs in a Nutshell

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  Improving the performance of AWS Glue jobs involves several strategies that target different aspects of the ETL (Extract, Transform, Load) process. Here are some key practices. 1. Optimize Job Scripts Partitioning : Ensure your data is properly partitioned. Partitioning divides your data into manageable chunks, allowing parallel processing and reducing the amount of data scanned. Filtering : Apply pushdown predicates to filter data early in the ETL process, reducing the amount of data processed downstream. Compression : Use compressed file formats (e.g., Parquet, ORC) for your data sources and sinks. These formats not only reduce storage costs but also improve I/O performance. Optimize Transformations : Minimize the number of transformations and actions in your script. Combine transformations where possible and use DataFrame APIs which are optimized for performance. 2. Use Appropriate Data Formats Parquet and ORC : These columnar formats are efficient for storage and querying, signif
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20 Best Videos to Learn Machine Learning Quickly

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According to Coursera -Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome.

1.     introduction, The Motivation Applications of Machine Learning
2.     An Application of Supervised Learning - Autonomous Deriving
3.     The Concept of Underfitting and Overfitting
4.     Newtons Method
5.     Discriminative Algorithms
6.     Multinomial Event Model
7.     Optimal Margin Classifier
8.     Kernels
9.     Bias/variance Tradeoff
10. Uniform Convergence - The Case of Infinite H
11. Bayesian Statistics and Regularization
12. The Concept of Unsupervised Learning
13. Mixture of Gaussian
14. The Factor Analysis Model
15. Latent Semantic Indexing (LSI)
16. Applications of Reinforcement Learning
17. Generalization to the Continuous States
18. State-action Rewards
19. Advice for Applying Machine Learning
20. Partially Observable MDPs (POMDPs)

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