Mahout Training in Kansas City

Mahout Training in Kansas City
Mahout - scalable machine learning and data mining courses

MO, Kansas City - Crown

Two Pershing Square, 2300 Main Street Suite 900
64108 Kansas , MO
United States
Missouri US
 MO, Kansas City - Crown
The venue is located right next to Union Station, in the vicinity of Washington Square Park and the Sheraton and Westin hotels.Read more

Mahout Course Events - Kansas City

Code Name Venue Duration Course Date PHP Course Price [Remote / Classroom]
apachemdev Apache Mahout for Developers MO, Kansas City - Crown 14 hours Thu, Jun 29 2017, 9:30 am $5500 / $7400
apachemdev Apache Mahout for Developers KS, Overland Park - Lighton Tower 14 hours Tue, Jul 11 2017, 9:30 am $5500 / $7160
apachemdev Apache Mahout for Developers MO, Kansas City - Crown 14 hours Wed, Aug 23 2017, 9:30 am $5500 / $7400
apachemdev Apache Mahout for Developers KS, Overland Park - Lighton Tower 14 hours Thu, Aug 31 2017, 9:30 am $5500 / $7160
apachemdev Apache Mahout for Developers MO, Kansas City - Crown 14 hours Thu, Oct 12 2017, 9:30 am $5500 / $7400
apachemdev Apache Mahout for Developers KS, Overland Park - Lighton Tower 14 hours Thu, Oct 26 2017, 9:30 am $5500 / $7160
apachemdev Apache Mahout for Developers MO, Kansas City - Crown 14 hours Wed, Dec 6 2017, 9:30 am $5500 / $7400
apachemdev Apache Mahout for Developers KS, Overland Park - Lighton Tower 14 hours Thu, Dec 21 2017, 9:30 am $5500 / $7160

Course Outlines

Code Name Duration Outline
apachemdev Apache Mahout for Developers 14 hours

Audience

Developers involved in projects that use machine learning with Apache Mahout.

Format

Hands on introduction to machine learning. The course is delivered in a lab format based on real world practical use cases.

Implementing Recommendation Systems with Mahout

  • Introduction to recommender systems
  • Representing recommender data
  • Making recommendation
  • Optimizing recommendation

Clustering

  • Basics of clustering
  • Data representation
  • Clustering algorithms
  • Clustering quality improvements
  • Optimizing clustering implementation
  • Application of clustering in real world

Classification

  • Basics of classification
  • Classifier training
  • Classifier quality improvements

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