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Artificial Intelligence with Python



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About this course

This comprehensive course on ‘Artificial Intelligence’ covers all the basics of neural network-based models. Get a conceptual understanding of learning mechanisms such as Need and history of neural networks, gradient, forward propagation, loss functions and its implementation using python libraries. Learn some essential concepts related to deep neural networks that also work with Google's powerful library Tensorflow which comes with pre built Keras. We will be covering all theoretical and practical aspects of this subject, in-depth. Dive deeper into the mathematics behind each concept to understand their specifics. We will conclude with a neural network model for classification using MNIST data set. Learn its application on business or real-life problems in other domains.

Skills covered

  • check Perceptron
  • check ANN
  • check Gradient
  • check Backpropagation
  • check Activation Functions
  • check Softmax Function

Course Syllabus

Artificial Intelligence with Python

  • play History behind neural networks
  • play Relationship between biological neuron and artificial neuron
  • play Perceptron and working mechanism
  • play Architecture of artificial neural network
  • play Types of activation functions
  • play Softmax function
  • play Forward propagation
  • play Loss function
  • play Demo using keras framework
  • play Back propagation and gradient descent
  • play Tensorflow 2.0
  • play Demo on MNIST data set

Course Certificate

Get Artificial Intelligence 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.

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