Deep Learning A-Z™:- Hands*On Artificial Neural Networks



What can you learn

  • Understand the conscience behind the artificial neural network.
  • Practically the use of artificial nerve networks.
  • Understand the convoluted neural network behind conscience.
  • Application of neural networks in practice
  • Understand the conscience behind repetitive neural networks.
  • Apply neural networks frequently to practice
  • Understand the conscience behind self-organized maps.
  • Apply practically self-organized approaches
  • Understand the conscience behind Boltzmann machines.
  • Practically applied screw machine
  • Understand the conscience behind Autoencoders.
  • Practically automatic encryption request.

Required

  • High school math level
  • Basics about Python programming

Attribute

*** As it was on Kickstarter ***

Artificial intelligence is on the rise. No doubt about that. Self-driving cars drive millions of miles, IBM Watson diagnoses patients better than an army of doctors and Google beats Alfago world champion in Deep Mind - a game in which intuition plays a key role.

But the more complex the AI, the more complex the problem must be. And only in-depth education can solve such complex problems, which is why it is at the heart of artificial intelligence.

--- Why Deep Learning A-Z? †

Here are five reasons why we think Deep Learning is really different from A-Z and different from other training programs:

1. Strong structure


What we primarily focus on is the structure of the curriculum. Deep learning is very broad and complex and you need to have a clear and global vision to navigate this maze.

Therefore, we have divided the chapter into two sections, which represent the two main branches of Deep Learning: Supervised Deep Learning and Non-Supervised Deep Learning. With a focus on three separate algorithms in each volume, we have the perfect structure for mastering deep learning.

2. Introductory Tutorial


Many courses and books bombard you with theory, math, and coding… but they forget to explain perhaps the most important thing: why you do what you do. And this course is very different. We focus on developing intuitive *experience* for the concepts behind the Deep Learning Algorithm.

With our intuitive lessons you can be sure that you have understood all the techniques on a natural level. And once you get into coding practice, you'll see for yourself how meaningful your experience will be. This is a game changer.

3. Interesting projects


Tired of courses based on overused, outdated datasets?

Yes? Then you are for healing.

In this lesson, we'll work on real-world datasets to solve real-world business problems. (Definitely no dull eyes or a set of statistical classification data we see in every course). In this course we solve ten real world challenges:

Artificial neural networks to solve customer problems
A Convolutive Neural Network for Image Recognition
Frequent neural network for forecasting stock prices
Self-organized cards to detect fraud
Boltzmann machine to make a recommended system
Auto Encoder Stacked to Complete the Netflix 1 Million Prize Challenge*
* Stacked auto-encoder is a completely new deep learning technique that only existed a few years ago. We don't need to go into detail about this method anywhere.

4. Hand coding


Deep learning A-Z. We're on your side Every practical lesson starts with a blank page and we write the code from scratch. That way you can follow and understand how the code is created and what each line means.

In addition, we deliberately set up the code so that you can download it and apply it to your project. In addition, we explain step by step how and where you can change the code to insert your dataset, algorithms to adapt your needs, to get the input you follow.

This is a course that extends your career naturally.

5. Course Support


Have you ever taken a course or read a book where you have questions but can't reach the author?

Well, this course is different. We are fully committed to creating the most useful and powerful in-depth learning curriculum in the world. It is your responsibility to be there when you need our help.

In fact, we need to eat and sleep physically, we have put together a team to help professional data scientists. When you ask a question, you will receive an answer from us within 48 hours.

No matter how complicated your question is, we go for it.

--- Tools ---

Tensorflow and Pytorch are two popular open source deep learning libraries. In this course you will learn both!

TensorFlow is developed by Google and is used in their speech recognition systems, new Google Photos products, Gmail, Google Search and more. Companies using Tensorflow include AirBnb, Airbus, Ebay, Intel, Uber and more than a dozen.

PyTorch is equally powerful and was developed by researchers from Nvidia and leading universities: Stanford, Oxford, Paris Tech.
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So which is better and why?

Well, in this course you will have the chance to work with both of you and understand when tensorflow is best and when PyTorch is the right choice. In all lessons, we compare the two and give you suggestions and ideas that work best in certain situations.


Here is the download links

https://www.udemy.com/course/deeplearning/
https://drive.google.com/file/d/1F2tBvQGNLC2WfNUuHlTyEkAwN07tJc_7/view?usp=sharing

* If your in trouble watch the video thanks! *


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