Plan Szkolenia

Introduction

  • Overview of Dask features and advantages
  • Parallel computing in Python

Getting Started

  • Installing Dask
  • Dask libraries, components, and APIs
  • Best practices and tips

Scaling NumPy, SciPy, and Pandas

  • Dask arrays examples and use cases
  • Chunks and blocked algorithms
  • Overlapping computations
  • SciPy stats and LinearOperator
  • Numpy slicing and assignment
  • DataFrames and Pandas

Dask Internals and Graphical UI

  • Supported interfaces
  • Scheduler and diagnostics
  • Analyzing performance
  • Graph computation

Optimizing and Deploying Dask

  • Setting up adaptive deployments
  • Connecting to remote data
  • Debugging parallel programs
  • Deploying Dask clusters
  • Working with GPUs
  • Deploying Dask on cloud environments

Troubleshooting

Summary and Next Steps

Wymagania

  • Experience with data analysis
  • Python programming experience

Audience

  • Data scientists
  • Software engineers
 14 godzin

Liczba uczestników



Cena za uczestnika

Opinie uczestników (2)

Szkolenia Powiązane

QGIS for Geographic Information System

21 godzin

Advanced Data Analysis with TIBCO Spotfire

14 godzin

Introduction to Spotfire

14 godzin

AI-Driven Data Analysis with TIBCO Spotfire X

14 godzin

Data Analysis with SQL, Python and Spotfire

14 godzin

Sensu: Beginner to Advanced

14 godzin

Monitoring Your Resources with Munin

7 godzin

Automated Monitoring with Zabbix

14 godzin

Fluentd for Log Data Unification

14 godzin

Nagios Certified Administrator Preparation

21 godzin

Advanced Nagios

21 godzin

Nagios

35 godzin

Nagios Core

21 godzin

Nagios Certified Professional Preparation

21 godzin

Nagios XI Administration

21 godzin

Powiązane Kategorie