Deep Learning with Python and Keras

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Last updated on November 22, 2024 6:38 am
Deep Learning with Python and Keras
Deep Learning with Python and Keras

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Deep Learning with Python and Keras

★★★★★
$99.99  in stock
Udemy.com
as of November 22, 2024 6:38 am

Understand and build Deep Learning models for images, text and more using Python and Keras

Created by: Data Weekends
Learn the essentials of Data Science in just one weekend
Created by: Jose Portilla
Head of Data Science at Pierian Training
Created by: Francesco Mosconi
CEO at Catalit & Zero to Deep Learning
Created by: Pierian Training
Data Science and Machine Learning Training
Rating:4.64 (3297reviews)     24539students enrolled

What Will I Learn?

  • To describe what Deep Learning is in a simple yet accurate way
  • To explain how deep learning can be used to build predictive models
  • To distinguish which practical applications can benefit from deep learning
  • To install and use Python and Keras to build deep learning models
  • To apply deep learning to solve supervised and unsupervised learning problems involving images, text, sound, time series and tabular data.
  • To build, train and use fully connected, convolutional and recurrent neural networks
  • To look at the internals of a deep learning model without intimidation and with the ability to tweak its parameters
  • To train and run models in the cloud using a GPU
  • To estimate training costs for large models
  • To re-use pre-trained models to shortcut training time and cost (transfer learning)

Requirements

  • Knowledge of Python, familiarity with control flow (if/else, for loops) and pythonic constructs (functions, classes, iterables, generators)
  • Use of bash shell (or equivalent command prompt) and basic commands to copy and move files
  • Basic knowledge of linear algebra (what is a vector, what is a matrix, how to calculate dot product)
  • Use of ssh to connect to a cloud computer

Target audience

  • Software engineers who are curious about data science and about the Deep Learning buzz and want to get a better understanding of it
  • Data scientists who are familiar with Machine Learning and want to develop a strong foundational knowledge of deep learning

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