Neural Networks: Deep Learning, Machine Learning, AI & NLP

 Description

Neural networks are computing systems inspired by the biological neural networks. Such systems improve themselves by considering examples, generally without task-specific programming. Instead, they evolve their own set of relevant characteristics from the learning material that they process, but if you don’t master neural networks, you will miss the opportunity to apply and work with neural networks.

What if you could change that?

My complete Neural Network course will show you the exact techniques and strategies you need to apply the intuition behind artificial neural networks, apply convolutional neural networks, do recurrent neural networks, have the Solutions to exploding and vanishing gradient.

For less than a movie ticket, you will get over 2.5 hours of video lectures and the freedom to ask me any questions regarding the course as you go through it. :)

What Is In This Course?

Your Neural Network Skills Will Be Much Easier.

Except if you’re an expert at Neural Network, know Types Of Neural Networks, work with Elman Networks And Jordan Networks, master RNN With Python, Numpy, And Theano, know Adaline (Adaptive Linear Neuron) and use Backpropagation Networks Architecture, you are going to lose many job/career opportunities or even miss working with conventional and recurrent neural networks.

As what Howard Rheingold, a critic, writer, and teacher on modern communication media such as the Internet, says “The neural network is this kind of technology that is not an algorithm, it is a network that has weights on it, and you can adjust the weights so that it learns. You teach it through trials.”

You can try it with no financial risk.

In This Neural Network Training, You'll Learn:

• Types Of Neural Networks.   
• The Neural Network Architecture
• Applications Of Neural Networks     
• Recurrent Neural Networks
• Hopfield Network      
• Elman Networks And Jordan Networks        
• Long-Term And Short-Term Memory           
• Gated Recurring Unit
• Application Of Recurrent Neural Networks 
• RNN With Python, Numpy, And Theano      
• Training Of Network With Theano And The GPU   
• Challenges And Solutions For Recurrent Neural Networks Training           
• Challenges Of Recurrent Neural Training
• Solutions To Exploding And Vanishing Gradient
• Xor Problem & Network       
• Perceptron Network   
• Multilayer Perceptron
• Adaline (Adaptive Linear Neuron)   
• Propagation And Stochastic Gradient Descent         
• Backpropagation Networks Architecture      
• Stochastic Gradient Descent 
• Sgd Implementation  
• Backpropagation Through Time (BPTT)      
• Implementation Of A Neural Network          
• Optical Character Recognition (OCR)          

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Is This For You?

• Do you want to apply the intuition behind artificial neural networks?
• Are you wondering how to apply convolutional neural networks?
• Do you know how to do recurrent neural networks?

Then this course will definitely help you.

This course is essential to all developers, programmers, coders, data analysts, computer scientists and anyone looking to master Neural Network.

I will show you precisely what to do to solve these situations with simple and easy techniques that anyone can apply.

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Why To Master Neural Network?

Let Me Show You Why To Master Neural Network:

1. You will apply the intuition behind artificial neural networks.

2. You will apply convolutional neural networks.

3. You will do recurrent neural networks.

4. You will have the Solutions to exploding and vanishing gradient.      

Thank you so much for taking the time to check out my course. You can be sure you're going to absolutely love it, and I can't wait to share my knowledge and experience with you inside it! 

Why wait any longer?

Click the green "Buy Now" button, and take my course 100% risk free now!

Who is the target audience?

• All Developers, Programmers, Coders, Data Analysts, Computer Scientists
• Anyone Looking To Master Neural Network.
• This Is Not For People Looking For Lazy Ways To Pass The Exam