In The Co-operative Exchange, we show the price in bitcoin (BTC) for educational purposes. This is in line with our vision, ‘Co-operatives for collective freedom, bitcoin for individual liberty.’ We believe that co-operation is the soundest form of human enterprise. We believe that bitcoin is sound money, money that cannot be corrupted nor controlled by anyone. We want to advance the cooperative circular economy and we agitate for innovation to fuel that, e.g. Starlink-Polaris for Cooperatives Initiative, CoopEnergy (100% Renewable), CoopShop and other crazy co-op things.
Refresh to see price in pesos (PHP). Checkout price is in pesos. But you will have an option to pay in pesos or bitcoin. You can use any Lightning wallet. Lightning is the fastest and cheapest way to send money anywhere in the world. We recommend CoopPay, the first co-op Lightning wallet in the world! Learn more using our sound money converter
Author: Damji, Jules
Brand: O'Reilly Media
Edition: 2
Binding: Paperback
Number Of Pages: 397
Release Date: 25-08-2020
Part Number: 37185636
Details: Data is bigger, arrives faster, and comes in a variety of formatsâ??and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark.
Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, youâ??ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow
EAN: 9781492050049
Package Dimensions: 9.2 x 7.0 x 1.6 inches
Languages: English