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Deep Learning with Python



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About this course

This comprehensive course on Deep Learning is all about understanding and implementing models based on neural networks. Learn some basic concepts such as need and history of neural networks, gradient, forward propagation, loss functions and its implementation from scratch using python libraries. Understand the essential concepts of deep neural networks that collaborate with Google's powerful library TensorFlow which comes with pre built Keras. We will dive deeper into the mathematics behind each of these concepts to understand them fully. In the end, conclude with a neural network model for classification using MNIST data set. Learn how the same concepts can be applied to business and real-life problems in other domains.

Skills covered

  • check ANN
  • check Tensorflow
  • check Keras
  • check Gradient
  • check Backpropagation

Course Syllabus

Deep Learning with Python

  • play Need for deep learning
  • play Introduction to Tensorflow
  • play Tensorflow :Eager execution and hello world
  • play Tensorflow:Modelling an equation in Tensorflow
  • play calculating loss and gradient
  • play Hands On: Regression using tensorflow(Eager Execution and Eager Normalization)
  • play Gradient
  • play Keras framework
  • play Classification using MNIST

Course Certificate

Get Deep Learning with Python course completion certificate from Great learning which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.

GL Academy Sample Certificate
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