The Visual Guide on How Neural Networks Learn from Data

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素材介绍

The Visual Guide on How Neural Networks Learn from Data

Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 48000 Hz, 2ch | Size: 497 MB

Genre: eLearning Video | Duration: 2.5 hour | Language: English + .srt

The BEST Resource for Understanding Neural Networks and How They Learn

What you'll learn

Understand what Neural Networks (NNs) are all about

Step-by-Step in-Motion NN files for you to KEEP, yes, these files are yours!

Adjust Templates to your requirements => SEE what's going on inside NNs!

See how Neural Networks LEARN (graphic and dynamic files), follow all causes and effects!

Understand KEY ALGORITHMS in NN's (Gradient Descent, Backpropagation and more)

Know Types of Neural Networks, Designs and Advanced Topics

Requirements

1. Excel and PowerPoint (Office 2010+)

2. Maths (Basics)

3. A Plus: Calculus and Derivatives (Optional, not required)

Description

What makes this course special:

Step-by-Step Neural Network Learning Process,

Master topics like Fundamentals, Objectives, Required Datasets, Weights, Biases, Nodes, Activation functions, Feed-Forward Passes, Predictions, Losses, Gradient Descent, Learning, Backpropagation and more!

Plus, personalized feedback and help. You ask, I answer directly!

This is your BEST resource for Neural Networks (NN) learning! A must for understanding special concepts and not get lost in computing your own NNs:

First:

You'll start the Neural Networks Primer with Fundamentals, Objectives, Data and more:

Learn concepts using analogies for maximum learning, so you will be fully covered.

Learning how NNs learn will be easy with this Primer under your sleeve!

Second:

You'll continue the NN Primer with Learning, Backpropagation and Predictions and more topics

In an easy and intuitive way, you will understand how they work,

This is fundamental in the NN Learning Process.

At the end of this section, you will have mastered the NN Primer!

Now, you are ready for the Step-by-Step (in-Motion) sections!

Third:

You'll start the in-Motion section with Inputs, Weights, Biases, Activations, Nodes and Feed-Forward Passes:

See how they work inside an NN,

Step-by-step templates, so you can follow every detail,

These files will be dynamic, so you'll understand how NNs work as numbers will be updated on-the-fly and right in front of your eyes.

Forth:

You'll continue with the in-Motion section with NN Learning, Backpropagation, Tuning and Prediction:

You will understand how NNs learn from the data.

This all part of the dynamic templates you get to keep.

You'll do several examples along the way for maximum learning.

Lastly, you'll see what NNs do to make the best predictions.

Fifth:

You'll finish the in-Motion section by doing a complete rundown on everyting you've learned so far:

You'll see how all NN inner components work for learning and prediction.

Pay close attention at how all parts adjust, making the NN learn in front of your eyes.

After this section, you will be fully versed on how NNs learn!

Sixth:

I will devote a section for more additional knowledge and resources for continous learning. And then, I will conclude with some Final Words.

What are the Requirements?

The only thing you'll need for this course is: Excel and PowerPoint: It is that easy!

You will also need to bring your Basic Maths too,

If you bring your Calculus (Derivatives) knowledge, that will be a big plus for you (but not required),

What are some of the Benefits?

As it is usual in my courses, you will get all files and spreadsheets for all lectures.

This way you can replicate everything I do immediately after each lecture.

Neural Networks are the new thing today.

With it, you can explore and engage Artificial Intelligence, which I recommend you to dive in as it's part of the future.

Plus, it's very rewarding and fun too!

New content coming in the near future, let me know yout thoughts.

Lastly, you can post questions or doubts, and I'll answer to you personally.

I hope you find this course as useful as I have creating it!

I'll see you inside,

-M.A. Mauricio M.

Who this course is for:

Once and For All => Learn and Understand Step-by-Step How Neural Networks work with this course

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