Neural Networks Explained: A Beginner's Guide to Deep Learning

In this video, we will talk about neural networks and some of their basic components! 🧠🧠🧠
Neural Networks are machine learning algorithms (sets of instructions) that we use to solve problems that traditional computer programs can barely handle! 🤯
For example Face Recognition, Object Detection and Image Classification.
We will take a very close look inside a typical classifier neural network and we will follow an input image from start to finish. The concepts we will cover are: NN, labels, computer vision, weights, hidden layers, training, narrow AI.

Have fun!!! and please don't forget to share if you find it useful! 💙💛💙

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🤓 Further Learning 🤓
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How Computers See Images: https://youtu.be/mAMTXJJQBDI
Draw Images with Open CV: https://youtu.be/PtvN8ad9N3g
Supervised Learning and more: https://youtu.be/mMc_PIemSnU

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⏳ Timestamps ⏳
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00:00 - What is a Neural Network
00:55 - How Computers See Images
02:20 - What is a Label
02:44 - Hidden Layers
03:48 - Training
04:10 - Weights
04:42 - Optimization
05:27 - Narrow AI
06:03 - Input Data
06:18 - Thanks for Watching!
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IN THE NEXT TUTORIAL:
We will learn how to use Pytorch to train neural networks on popular computer vision databases!
We will implement with Python all the concepts we have learned in this video and it's gonna be really really fun! I promise!! 😊

All the beautiful icons in this video and thumbnail are by freepik.com and flaticon.com! 🤩