Udemy How to learn machine learning and neural networks Udemy
Price: USD 200
  • Duration: Flexible

Course details

  1. What is machine learning / ai (artificial intelligence)?
  2. How to apply and learn machine learning in practice ?
  3. What are neural networks ?
  4. What is deep learning?
  5. What kind of neural networks exist?
  6. What are multilayer perceptrons , what are convolutional neural networks ? How do cnns work?
  7. What are recurrent neural networks ( rnn ), what are long short term neural networks ( lstm )and how do the work?

If you need answers to one or more of these questions, you have come to the right place!

Machine learning and neural networks are the hottest topic out there. Self driving cars, image recognition, ecommerce, predicting customer behavior, stock market predictions, you name it!

Google, Facebook, Tesla, Amazon, Alibaba,... all great companies are working on this topic.

machine learning and neural networks are everywhere and will determine the world of tomorrow.Because of that we all should familiarize ourselves with this topic. If we do so, we will create tremendous opportunities and lay the foundation to a bright future.

Especially as a beginner, it's difficult to get into machine learning and neural networks and there are a lot of questions to ask. Because of that I created this new in depth course to help you get started and equip you with all knowlege you require to go from beginner to advanced. This course provides you with more than 10 hours of highly valuable content. Together we address theory as well as apply this knowlege in practice because only applied knowlege is real knowledge.

Together we will apply various machine learning algorithms anddeep learning neural networks in practice. All other resources you need to follow along can be acquired for free and will be shown at the beginning of the couse.

After finishing the course you have acquired a solid foundation which you could leverage in your future career.

Let's get into it.

Updated on 14 November, 2018
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