Machine Learning at Scale

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