Deep Learning Fundamentals

Overview:

    Relatively obscure a few short years ago, Deep Learning is ubiquitous today across data-driven applications as diverse as machine vision, natural language processing, and super-human game-playing.

    This Deep Learning primer brings the revolutionary machine-learning approach behind contemporary artificial intelligence to life with interactive demos featuring Keras, the leading high-level Deep Learning library.

    To facilitate an intuitive understanding of Deep Learning’s artificial-neural-network foundations, essential theory will be introduced visually and pragmatically. Paired with tips for overcoming common pitfalls and hands-on code run-throughs provided in straightforward Jupyter notebooks, this foundational knowledge empowers you to build powerful state-of-the-art Deep Learning models.

    Duration: 

    40 hours

    Course Objectives:

      Upon completion of this course, you will be able to:

      • Understand the language and fundamentals of artificial neural networks
      • Straightforwardly build TensorFlow Deep Learning models using the Keras API
      • Interpret the output of Deep Learning models to troubleshoot and improve results
      Intended Audience:
      • You work with data and want to be exposed to the range of applications of Deep Learning approaches.
      • You want to understand how Deep Learning works.
      • You want to create machine-learning models well-suited to solving a broad range of problems, including complex, non-linear problems with large, high-dimensional data sets.
      Prerequisites:
      • Experience analyzing data in Python
      • If you’re the kind of person who likes to be extra-prepared or you can’t wait to get started with Deep Learning
      Course outlines:

      1.      Module 1: The Unreasonable Effectiveness of Deep Learning

      • Training Overview
      • Introduction to Neural Networks and Deep Learning
      • The Deep Learning Families and Libraries

      2.      Module 2: Essential Deep Learning Theory

      • The Cart Before the Horse: A Shallow Neural Network in Keras
      • Learning with Artificial Neurons
      • TensorFlow Playground—Visualizing a Deep Net in Action

      3.      Module 3: Deep Learning with Keras, TensorFlow’s High-Level API

      • Revisiting our Shallow Neural Network
      • Deep Nets in Keras
      • What to Study Next, Depending on Your Interests
      • Học tại Hồ Chí Minh

      • Học tại Hà Nội

      • Học trực tuyến


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