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How to Create Deep Learning Algorithms in Python

How to Create Deep Learning Algorithms in Python (view)- Deep learning is the branch of machine learning where artificial neural networks, algorithms inspired by the human brain, learn by large amounts of data. As we learn from experiences,similarly the deep learning algorithm perform a task repeatedly. Deep learning refer because the neural networks have various (deep) layers that enable learning. Necessity of thought is required to overcome any problem, similarly there are many layers in neural networks which enable learning.

If you really want to learn from this course, you just have knowledge of high school mathematics and basic Python programming knowledge.

In this, you will learn the topics :

  • Understand the intuition behind Artificial Neural Networks and Convolutional Neural Networks
  • How to apply Artificial Neural Networks and Convolutional Neural Networks in practice
  • Understand the intuition behind Recurrent Neural Networks and Self-Organizing Maps
  • How to apply Recurrent Neural Networks and Boltzmann Machines work in practice
  • Understand the intuition behind Boltzmann Machines and AutoEncoders

   This course has total 185 lectures and it’s lecture divided into 6 parts :-

  1. Artificial Neural Networks 
  2. Convolutional Neural Networks
  3. Recurrent Neural Networks
  4. Self-Organizing Maps
  5. Boltzmann Machines
  6. AutoEncoders

There are Supervised and Unsupervised Deep Learning. Check below :-

SUPERVISED DL UNSUPERVISED DL
  • Artificial Neural Networks
  • Self-Organizing Maps
  • Convolutional Neural Network
  • Boltzmann Machines
  • Recurrent Neural Networks
  • AutoEncoders

 

In Artificial Neural Networks Intuition

  • ANN Intuition
  • Building an ANN
  • Evaluating, Improving and Tuning the ANN

 Convolutional Neural Networks

  • CNN Intuition
  • Building a CNN
  • Homework – What’s that pet ?
  • Evaluating, Improving and Tuning the CNN

 Recurrent Neural Networks

  • RNN Intuition
  • Building a RNN
  • Evaluating, Improving and Tuning the RNN

 Self-Organizing Maps

  • SOMs Intuition
  • Building a SOM
  • Mega Case Study

 Boltzmann Machines

  • Boltzmann Machine Intuition
  • Building a Boltzmann Machine

 AutoEncoders

  • AutoEncoders Intuition
  • Building an AutoEncoder

 It has also the Machine Learning Basics Lectures

  • Regression & Classification Intuition
  • Data Preprocessing Template
  • Classification Template
  • Bonus Lectures

Kirill Eremenko, Hadelin de Ponteves and Super Data Science Team are instructors are of this course.

Mr. Kirill Eremenko is a Data Science management consultant with five years of experience in finance, retail and other industries. He is trained by the best analytics mentors in Deloitte Australia.

Hadelin de Ponteves is the CEO and co-founder at BlueLife AI. He is an online entrepreneur who has created 50+ top-rated educational e-courses to the world. He have done 1M+ sales in 204 countries.

This course rating is 4.5 ( from 27k+ ratings) and  207k+ students are already enrolled in it. It is also available in 6 different languages such as English, French, German, Spanish, Italian and Portuguese. Instructors has updated it last on Feb, 2020. This has 22.5 hours on-demand video with 34 articles and 2 downloadable resources. You can use it for full lifetime access. It is accessible on mobile and TV.

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