Tensorflow 2 & Keras:Deep Learning & Artificial Intelligence

Tensorflow 2 & Keras:Deep Learning & Artificial Intelligence

Deep Learning & Artificial Intelligence with Tensorflow 2 & Keras, Neural Networks, GANs,Autoencoders, Deep Learning A-Z

Welcome to Deep Learning and Artificial Intelligence with Tensorflow 2 and Keras API Course.

This course includes how to work with tensorflow 2 and creates Deep Learning applications with tensorflow 2 and Keras.

This course guide you how to work with google colab, all the hands on work done in google colab.

Many Projects included in this course like MNIST Digits Classification, MNIST Fashion data classification, Cat and Dog images Classification, Facial Expression Recognition, Leaf disease recognition, Generate Images with DCGANs(Deep Convolutional Generative Adversarial Networks) with Keras, Denoising autoencoders with Keras, TensorFlow, and Deep Learning etc.

Generative Deep Learning – Neural Style Transfer also included in this course.

For every lecture reference notes and code file is attached in this course.

Tensorflow is an open source machine library, and is one of the most widely used frameworks for deep learning.

Google released a new version of their TensorFlow deep learning library (TensorFlow 2) that integrated the Keras API directly and promoted this interface as the default or standard interface for deep learning development on the platform.

This course includes various topics –

  • Complete Understanding of TensorFlow 2.0 (Google’s Deep Learning Framework)from the Scratch
  • Keras API to quickly build models that run on Tensorflow 2
  • Learn How Neural Network works
  • Understand Backpropagation, Forward Propogation, Gradient Descent
  • Artificial Neural Networks (ANNs)
  • Convolutional Neural Networks (CNNs)
  • Perform Image Classification with Convolutional Neural Networks
  • Image Recognition
  • Recurrent Neural Networks (RNNs)
  • Transfer Learning
  • Create Generative Adversarial Networks (GANs) with TensorFlow
  • Autoencoders
  • Introduction to Natural Language Processing
  • Data Analysis with Numpy, Pandas and Data Visualization with Matplotlib

Who this course is for:

  • Anyone Passionate about Deep Learning and Artificial Intelligence
  • Python Developer curious about Deep Learning and Tensorflow


  • Understanding of Python coding

Last Updated 5/2021


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