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Neural Networks with Tensorflow – Web Courses

Neural Networks with Tensorflow - Web Courses
Neural Networks with Tensorflow - Web Courses

Neural Networks with Tensorflow – Web Courses

A Primer

What you’ll learn

Neural Networks with Tensorflow – Web Courses

  • Building Neural Networks with Tensorflow

Requirements

  • You should know Python programming, have basic math knowledge, and basic concepts of machine learning before enrolling.

Description

You’re going to learn the most popular library to build networks and machine learning algorithms.

In this hands-on, practical course, you will be working your way through with Python, Tensorflow, and Jupyter notebooks.

What you will learn:

  • Basics of Tensorflow
  • Artificial Neurons
  • Feed Forward Neural Networks
  • Activations and Softmax Output
  • Gradient Descent
  • Backpropagation
  • Loss Function
  • MSE
  • Model Optimization
  • Cross-Entropy
  • Linear Regression
  • Logistic Regression
  • Convolutional Neural Networks (with examples)
  • Text and Sequence Data
  • Recurrent Neural Networks (with examples)
  • Neural Style Transfer (in progress)

Who this course is for:

  • You want to get into machine learning and artificial neural networks
  • You already work in ML/AI and need to learn Tensorflow
  • Who student, know some coding, and want to get into machine learning
  • Last updated 12/2020
Machine Learning Course
Content From: https://www.udemy.com/course/tensorflownets/
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