Intro to Machine Learning with TensorFlow

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Intro to Machine Learning with TensorFlow provided by Udacity is a comprehensive online course, which lasts for 13 weeks long, 10 hours a week. Intro to Machine Learning with TensorFlow is taught by Cezanne Camacho, Mat Leonard, Luis Serrano, Dan Romuald Mbanga, Jennifer Staab, Sean Carrell, Josh Bernhard , Jay Alammar, Andrew Paster, Juan Delgado and Michael Virgo. Upon completion of the course, you can receive an e-certificate from Udacity. The course is taught in Englishand is Paid Course. Visit the course page at Udacity for detailed price information.

Overview
  • In LinkedIn’s 2020 Emerging Jobs report, AI Specialist, a role that includes machine learning, deep learning, TensorFlow, and Python as key skills, boasts 74% annual growth. All of the above skills are incorporated into Udacity’s Intro to Machine Learning with TensorFlow Nanodegree program, which is a great way to get introduced to the fundamentals of machine learning, including areas like manipulating data, supervised & unsupervised learning, and deep learning. In this program, you will complete three hands-on projects including building an image classifier, and creating customer segments, that will prepare you for one of the 50,000 open roles in machine learning.
    Build a solid foundation in Supervised, Unsupervised, and Deep Learning. Then, use these skills to test and deploy machine learning models in a production environment.

Syllabus
    • Supervised Learning
      • In this lesson, you will learn about supervised learning, a common class of methods for model construction.
    • Deep Learning
      • In this lesson, you will learn the foundations of neural network design and training in TensorFlow.
    • Unsupervised Learning
      • In this lesson, you will learn to implement unsupervised learning methods for different kinds of problem domains.