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Course Skill Level:


Course Duration:

3 day/s

  • Course Delivery Format:

    Live, instructor-led.

  • Course Category:

    AI / Machine Learning

  • Course Code:


Who should attend & recommended skills:

Linux experienced participants seeking exploration of supervised and unsupervised learning to add smart features to apps

Who should attend & recommended skills

  • This course is geared for attendees who wish to Explore supervised and unsupervised learning techniques and add smart features to your applications.
  • Skill-level: Foundation-level C# Machine Learning skills for Intermediate skilled team members. This is not a basic class.
  • Linux: Basic (1-2 years’ experience), including familiarity with command-line options such as ls, cd, cp, and su

About this course

The necessity for machine learning is everywhere, and most production enterprise applications are written in C# using tools such as Visual Studio, SQL Server, and Microsoft Azur2e. Hands-On Machine Learning with C# uniquely blends together an understanding of various machine learning concepts, techniques of machine learning, and various available machine learning tools through which users can add intelligent features. These tools include image and motion detection, Bayes intuition, and deep learning, to C# .NET applications. Using this course, you will learn to implement supervised and unsupervised learning algorithms and will be better equipped to create excellent predictive models. In addition, you will learn both supervised and unsupervised forms of regression, mainly logistic and linear regression, in depth. Next, you will use the nuML machine learning framework to learn how to create a simple decision tree. In the concluding lessons, you will use the Accord.Net machine learning framework to learn sequence recognition of handwritten numbers using dynamic time warping. We will also cover advanced concepts such as artificial neural networks, autoencoders, and reinforcement learning. By the end of this course, you will have developed a machine learning mindset and will be able to leverage C# tools, techniques, and packages to build smart, predictive, and real-world business applications.

Skills acquired & topics covered

  • Working in a hands-on learning environment, led by our C# Machine Learning expert instructor, students will learn about and explore:
  • Leveraging machine learning techniques to build real-world applications
  • Using the Accord.NET machine learning framework for reinforcement learning
  • Implementing machine learning techniques using Accord, nuML, and Encog
  • Learning to parameterize a probabilistic problem
  • Using Naive Bayes to visually plot and analyze data
  • Plotting a text-based representation of a decision tree using nuML
  • Using the Accord.NET machine learning framework for associative rule-based learning
  • Developing machine learning algorithms utilizing fuzzy logic
  • Exploring support vector machines for image recognition
  • Understanding dynamic time warping for sequence recognition

Course breakdown / modules

  • The importance of artificial intelligence
  • The emergence of the cloud
  • The Microsoft cloud Azure

  • TDSP stages
  • Tools for TDSP

  • Cognitive Services for Vision APIs
  • The Computer Vision API
  • Face API
  • Cognitive Services for Language APIs
  • Cognitive Services for Speech APIs
  • Cognitive Services for Knowledge APIs
  • Cognitive Services for Search APIs

  • What is a bot?
  • Creating a bot with Bot Service

  • Deploying an Azure AI Gallery template
  • Building an experiment
  • Deploying a model as a web service

  • Different scalable compute options in Azure
  • Introduction to DSVMs
  • DLVM
  • Batch AI service
  • ACI
  • AKS

  • What is Microsoft ML Server?
  • Machine learning with Python