In this Machine Learning experts will help on and goes beyond the collect-and-analyze phase of big data by focusing on how machine learning algorithms can be rewritten and extended to scale to work on petabytes of data, both structured and unstructured, to generate sophisticated models used for real-time predictions.
Advanced Data Wrangling at Scale (Big Pandas, Advanced SQL)
Scalable Machine Learning with Dask
Distributed Computing with Dask
Parallel Computing with Dask
ML at Scale on Spark
MLSupervised Learning with Spark
MLRecommendation Engines at Scale with Spark
Monitoring and Debugging Scaleable
ML SystemsBuilding, Debugging and Tuning Spark
ML Pipeline
Best Practices for ML at Scale