By Padma Priya Chitturi
- Use Apache Spark for info processing with those hands-on recipes
- Implement end-to-end, large-scale facts research greater than ever before
- Work with strong libraries akin to MLLib, SciPy, NumPy, and Pandas to realize insights out of your data
Spark has emerged because the such a lot promising great facts analytics engine for information technology execs. the real strength and cost of Apache Spark lies in its skill to execute info technology projects with pace and accuracy. Spark's promoting element is that it combines ETL, batch analytics, real-time circulate research, computer studying, graph processing, and visualizations. It enables you to take on the complexities that include uncooked unstructured info units with ease.
This consultant gets you cozy and assured acting facts technology initiatives with Spark. you are going to find out about implementations together with dispensed deep studying, numerical computing, and scalable computing device studying. you'll be proven potent options to complicated options in information technology utilizing Spark's information technological know-how libraries reminiscent of MLLib, Pandas, NumPy, SciPy, and extra. those easy and effective recipes will assist you to enforce algorithms and optimize your work.
What you are going to learn
- Explore the subjects of information mining, textual content mining, ordinary Language Processing, info retrieval, and computer learning.
- Solve real-world analytical issues of huge info sets.
- Address info technology demanding situations with analytical instruments on a dispensed method like Spark (apt for iterative algorithms), which deals in-memory processing and extra flexibility for info research at scale.
- Get hands-on adventure with algorithms like class, regression, and advice on actual datasets utilizing Spark MLLib package.
- Learn approximately numerical and clinical computing utilizing NumPy and SciPy on Spark.
- Use Predictive version Markup Language (PMML) in Spark for statistical info mining models.
About the Author
Padma Priya Chitturi is Analytics Lead at Fractal Analytics Pvt Ltd and has over 5 years of expertise in great information processing. at the moment, she is a part of power improvement at Fractal and accountable for answer improvement for analytical difficulties throughout a number of company domain names at huge scale. ahead of this, she labored for an airways product on a real-time processing platform serving 1000000 consumer requests/sec at Amadeus software program Labs. She has labored on understanding large-scale deep networks (Jeffrey dean's paintings in Google mind) for picture type at the tremendous facts platform Spark. She works heavily with tremendous information applied sciences comparable to Spark, hurricane, Cassandra and Hadoop. She used to be an open resource contributor to Apache Storm.
Table of Contents
- Big information Analytics with Spark
- Tricky facts with Spark
- Data research with Spark
- Clustering, category, and Regression
- Working with Spark MLlib
- NLP with Spark
- Working with glowing Water - H2O
- Data Visualization with Spark
- Deep studying on Spark
- Working with SparkR
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Apache Spark for Data Science Cookbook by Padma Priya Chitturi