Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Udemy

Artificial Neural Networks(ANN) Made Easy

via Udemy

Overview

Learn ANN Model Building and Fine-tuning ANN hyper-parameters on Python and TensorFlow

What you'll learn:
  • ANN Introduction
  • ANN Model Building
  • ANN Hyper parameters
  • Fine-tuning and Selecting ANN models
  • Shallow and Deep Neural Networks
  • Building ANN Models in Python, TensorFlow and Keras

Course Covers below topics in detail

  • Quick recap of model building and validation

  • Introduction to ANN

  • Hidden Layers in ANN

  • Back Propagation in ANN

  • ANNmodel building on Python

  • TensorFlow Introduction

  • BuildingANNmodels in TensorFlow

  • Keras Introduction

  • ANNhyper-parameters

  • Regularization in ANN

  • Activation functions

  • Learning Rate and Momentum

  • Optimization Algorithms

  • Basics of Deep Learning

Pre-requite for the course.

  • You need to know basics of python coding

  • You should have working experience on python packages like Pandas, Sk-learn

  • You need to have basic knowledge on Regression and Logistic Regression

  • You must know model validation metrics like accuracy, confusion matrix

  • You must know concepts like over-fitting and under-fitting

  • In simple terms, Our Machine Learning Made Easy course on Python is the pre-requite.

Other Details

  • Datasets, Code and PPT are available in the resources section within the first lecture video of each session.

  • Code has been written and tested with latest and stable version of python and tensor-flow as of Sep2018

Taught by

Statinfer Solutions

Reviews

3.8 rating at Udemy based on 75 ratings

Start your review of Artificial Neural Networks(ANN) Made Easy

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.