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EncartaLabs

Machine Learning on iOS with Core ML

( Duration: 3 Days )

Core ML 3 integrates a broad variety of machine learning model types into your app and also enables advanced neural networks with support for over 100 layer types, and seamlessly takes advantage of the CPU, GPU, and Neural Engine to provide maximum performance and efficiency. You can run machine learning models directly on the device

By attending Machine Learning with Core ML workshop, delegates will learn:

  • What is Core ML
  • Vision and NLP Frameworks
  • Convert your models to Core ML models
  • Image Classification with Core ML
  • Text Recognition with Core ML

  • Familiar with Machine Learning concepts, Python and Swift programming languages
This Machine Learning with Core ML training course is ideal for:
  • Data Scientists
  • Computer Vision Engineers
  • Machine Learning Engineers and Developers

COURSE AGENDA

1

Overview of Machine Learning and Core ML

  • Introduction to Machine Learning and Deep Learning
  • Server Side vs Client Sider ML Applications
  • Overview of Core ML
2

Integrating a Core ML Model into Your App

  • Convert Trained Model to Core ML
  • Integrate Core ML Model to your Apps
3

Computer Vision with Core ML

  • Core ML Vision Models
  • Create your Core ML Vision App
  • Test out your Core ML Vision App
4

NLP with Core ML

  • Core ML NLP Models
  • Create a Core ML NLP App
  • Test out Core ML App

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 6,000 various courses on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

View our other course offerings by visiting https://www.encartalabs.com/course-catalogue-all.php

Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.

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