Deep Learning with TensorFlow

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Everyone who wishes to enhance their career in TensorFlow

Certificate

Module 1 – Introduction to TensorFlow

• HelloWorld with TensorFlow

• Linear Regression

• Nonlinear Regression

• Logistic Regression

• Activation Functions

Module 2 – Convolutional Neural Networks (CNN)

• CNN History

• Understanding CNNs

• CNN Application

Module 3 – Recurrent Neural Networks (RNN)

• Intro to RNN Model

• Long Short-Term memory (LSTM)

• Recursive Neural Tensor Network Theory

• Recurrent Neural Network Model

Module 4 - Unsupervised Learning

• Applications of Unsupervised Learning

• Restricted Boltzmann Machine

• Collaborative Filtering with RBM

Module 5 - Autoencoders

• Introduction to Autoencoders and Applications

• Autoencoders

• Deep Belief Network

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