Today we're going to talk big picture about what Neural Networks are and how they work. Neural Networks, which are computer models that act like neurons in the human brain, are really popular right now - they're being used in everything from self-driving cars and Snapchat filters to even creating original art! As data gets bigger and bigger neural networks will likely play an increasingly important role in helping us make sense of all that data.

Special thanks to Max Deutsch giving us permission to use his Neural Network-written Harry Potter chapter in this episode! Read more about his work here:
https://medium.com/deep-writin....g/harry-potter-writt

Neural Network to create anime characters:
https://arxiv.org/pdf/1708.05509.pdf

Neural Network to great Van Gogh-like art:
https://towardsdatascience.com..../gangogh-creating-ar

Neural Network to create skate decks:
https://github.com/RJT1990/gandecks/

Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/crashcourse

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Kaggle notebook with all the code: https://www.kaggle.com/wwsalmo....n/simple-mnist-nn-fr

Blog article with more/clearer math explanation: https://www.samsonzhang.com/20....20/11/24/understandi

Just what is happening inside a Convolutional Neural Network? Dr Mike Pound shows us the images in between the input and the result.

How Blurs & Filters Work (Kernel Convolutions): https://youtu.be/C_zFhWdM4ic
Cookie Stealing: https://youtu.be/T1QEs3mdJoc
Rob Miles on Game Playing AI: https://youtu.be/5oXyibEgJr0
Secure Web Browsing: https://www.youtube.com/watch?v=E_wX40fQwEA
Deep Learning: https://youtu.be/l42lr8AlrHk


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This video was filmed and edited by Sean Riley.

Computer Science at the University of Nottingham: http://bit.ly/nottscomputer

Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.com

In this project I built a neural network and trained it to play Snake using a genetic algorithm.

Thanks for watching! Subscribe if you enjoyed and Share if you know anyone who would be interested!

GitHub Repo: https://github.com/greerviau/SnakeAI
Twitter: https://twitter.com/greerviau
Support me on Patreon: https://www.patreon.com/greerviau

Thanks to Josh Cominelli for the music!
Soundcloud: https://soundcloud.com/josh-cominelli

Exploring how neural networks learn by programming one from scratch in C#, and then attempting to teach it to recognize various doodles and images.

Source code: https://github.com/SebLague/Ne....ural-Network-Experim
Demo: https://sebastian.itch.io/neur....al-network-experimen

If you'd like to support me in creating more videos (and get early access to new stuff), you can join my patreon here: https://www.patreon.com/SebastianLague

The data is from:
Digits http://yann.lecun.com/exdb/mnist/
Fashion https://github.com/zalandoresearch/fashion-mnist
Doodles https://github.com/googlecreat....ivelab/quickdraw-dat
Cifar10 https://www.cs.toronto.edu/~kriz/cifar.html

Chapters
0:00 Introduction
2:39 The decision boundary
3:49 Weights
5:42 Biases
6:45 Hidden layers
7:45 Programming the network
9:57 Activation functions
12:42 Cost
15:07 Gradient descent example
18:22 The cost landscape
19:55 Programming gradient descent
21:10 It's learning! (slowly)
23:21 Calculus example
27:34 The chain rule
29:50 Some partial derivatives
33:14 Backpropagation
39:25 Digit recognition
43:56 Drawing our own digits
47:37 Fashion
48:25 Doodles
52:00 The final challenge

Music:
Cosmic Waves - Michael FK
Amber - The Stolen Orchestra
Beyond the Horizon - Sounds Like Sander
Air - Assaf Ayalon
Purest Form - Sounds Like Sander
Hear Wide Open - Sounds Like Sander
Universal Wonder - Moments
Roman P - Moments
All In Good Time - Shimmer
It Will Come Back - The Stolen Orchestra
Frontier - Shimmer
New Moon - Cloud Wave
Sunflower - Cody Martin
Inner Peace - Moments
Enchanted - Cody Martin
Just Around The Corner - Shimmer

If you know nothing about how a neural network works, this is the video for you! I've worked for weeks to find ways to explain this in a way that is easy to understand for beginners.


Past Videos:
Intro to Machine Learning with Javascript:
https://www.youtube.com/watch?v=9Hz3P1VgLz4&list=PLoYCgNOIyGABWLy_XoLSxTVRe2bltV8GM&index=2&t=0s

Machine Learning 2 - Building a Recommendation Engine:
https://www.youtube.com/watch?v=lvzekeBQsSo&list=PLoYCgNOIyGABWLy_XoLSxTVRe2bltV8GM&index=3&t=0s

Machine learning and neural networks are awesome. This video provides beginners with an easy tutorial explaining how a neural network works - what math is involved, and a step by step explanation of how the data moves through the network.

The example used will be a feed forward neural network with back propagation. It explains the difference between linear and non linear data, the importance of the activation function, learning rate, and momentum configurations.

-~-~~-~~~-~~-~-
Also watch: "Tailwind CSS - why CSS utility classes save so much time"
https://www.youtube.com/watch?v=oU5ar0dmQEY
-~-~~-~~~-~~-~-

A video about neural networks, how they work, and why they're useful.

My twitter: https://twitter.com/max_romana

SOURCES
Neural network playground: https://playground.tensorflow.org/

Universal Function Approximation:
Proof: https://cognitivemedium.com/ma....gic_paper/assets/Hor
Covering ReLUs: https://proceedings.neurips.cc..../paper/2017/hash/32c
Covering discontinuous functions: https://arxiv.org/pdf/2012.03016.pdf

Turing Completeness:
Networks of infinite size are turing complete: Neural Computability I & II (behind a paywall unfourtunately, but is cited in following paper)
RNNs are turing complete: https://binds.cs.umass.edu/pap....ers/1992_Siegelmann_
Transformers are turing complete: https://arxiv.org/abs/2103.05247

More on backpropagation:
https://www.youtube.com/watch?v=Ilg3gGewQ5U

More on the mandelbrot set:
https://www.youtube.com/watch?v=NGMRB4O922I

Additional Sources:
Neat explanation of universal function approximation proof: https://www.youtube.com/watch?v=Ijqkc7OLenI
Where I got the hard coded parameters: https://towardsdatascience.com..../can-neural-networks

Reviewers:
Andrew Carr https://twitter.com/andrew_n_carr
Connor Christopherson

TIMESTAMPS
(0:00) Intro
(0:27) Functions
(2:31) Neurons
(4:25) Activation Functions
(6:36) NNs can learn anything
(8:31) NNs can't learn anything
(9:35) ...but they can learn a lot

MUSIC
https://www.youtube.com/watch?v=SmkUY_B9fGg

Neural Networks → https://ibm.biz/Neural_Networks_Now
Let's Create Data Fabric Instead of Data Silos → https://ibm.biz/Your_data_fabric

Neural networks reflect the behavior of the human brain, allowing computer programs to recognize patterns and solve common problems in the fields of AI, machine learning, and deep learning. Master Inventor, Martin Keen, makes some important points about neural networks and does it all in 5 minutes.

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Hi data nerds! Today I’m sharing with you my recommended learning roadmap and the courses to help you learn the core data science skills quickly. Resources are abundant online, but it is hard sometimes to select what is right for you, and what you really need. I hope with this learning roadmap, you can learn the most in-demand skills in the most effective way. Hope you enjoy it!

Thank you for watching and have a great day! 🤗

🔑 TIMESTAMPS
================================
0:00 - Intro
0:17 - My data science journey 🤓
2:12 - Google Data Analytics Professional cert
4:14 - Learn SQL Basic for DS Specialization
6:37 - Applied Data Science with Python Specialization
8:34 - Mathematics for Machine Learning Specialisation
10:50 - Data Visualisation with Tableau Specialisation
13:45 - Tips for saving $$


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In this video I will give you the resources you need to learn data science from zero knowledge. We will discuss several programming books and math books that are perfect for beginners who want to acquire the skills to become a data scientist. In particular we will look at books on R, Python, Calculus, Linear Algebra, and Statistics. Several more advanced books are also presented in this video. Do you have any other book recommendations for learning Data Science? If so, please leave a comment below.

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Notes of this Lecture:

Since Big Data, Data Science, and Data Analytics are emerging technologies (they’re still evolving), we often use Data Science and Data Analytics interchangeably. Let's clear this famous misunderstanding and clarify the difference between data science vs data analytics.

Recommended Videos,
9 Top Data Science Certifications to Boost Your Career in 2021
https://www.youtube.com/watch?v=eAaYbiBRTxQ

Difference Between AI vs ML vs DL vs Data Science Explained
https://www.youtube.com/watch?v=vtoKf-aJSs8

How to Learn Data Science Step by Step for FREE
https://www.youtube.com/watch?v=mJxGLvirQQI

11 Best Python Packages for Data Science
https://www.youtube.com/watch?v=cS0TaZV3gmU

5 Top Skills Needed for Machine Learning Engineer
https://www.youtube.com/watch?v=NdqVOHDJGD8

When NOT to use Machine Learning (ML) or Artificial Intelligence (AI)
https://www.youtube.com/watch?v=BZUHsuE2Rns

10+ ML & AI Career Path with Salaries | How to Start Career in AI and ML
https://www.youtube.com/watch?v=oQBUH0fB1mA

Got feedback on this video of data analytics vs data science? Feel free to share your views in the comment section below.

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#Shorts #YouTubeShorts #DataScience #DataAnalytics #60SecondsWhiteboard #DataAnalyst #DataScientist

Learn the basic components of Data Science in this crash course for beginners.
If you want to learn more about data science after completing this course, check out Max's Free Getting Started with Data Science Workshop: https://codingwithmax.com/webinar/data-scientist/

In this course for beginners, you will learn about:

1. Statistics: we talk about the types of data you'll encounter, types of averages, variance, standard deviation, correlation, and more.

2. Data visualization: we talk about why we need to visualize our data, and the different ways of doing it (1 variable graphs, 2 variable graphs and 3 variable graphs.)

3. Programming: we talk about why programming helps us with data science including the ease of automation and recommended Python libraries for you to get started with data science.

⭐️ Contents ⭐️
⌨️ (0:00:00) Introduction
⌨️ (0:10:52) Statistical Data Types
⌨️ (0:25:10) Types of Averages
⌨️ (0:38:55) Spread of Data
⌨️ (0:50:54) Quantiles and Percentiles
⌨️ (0:55:52) Importance of Data Visualization
⌨️ (1:05:14) One Variable Graphs
⌨️ (1:12:04) Two Variable Graphs
⌨️ (1:25:08) Three and Higher Variable Graphs
⌨️ (1:31:20) Programming

Course from Coding With Max. Check out the Coding With Max blog: https://www.codingwithmax.com/blog
Full data science course: https://codingwithmax.teachabl....e.com/p/data-scienti

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You want to learn what Data Science is? And you like brief explanations? Then this is the perfect video for you!

Video Timestamps:
0:00-0:23 Video intro
0:23-0:50 Why the data science notion is still confusing to people
0:50-1:09 Data science is an interdisciplinary field
1:09-1:35 Data science and AI
1:35-1:46 Data science, ML, Deep Learning
1:46-2:09 Channel promo
2:09-2:19 What you will see next
2:19-2:51 Types of data used
2:51-3:36 Activities performed by data scientists
3:36-3:54 Time allocation
3:54-4:06 Key skills needed by data scientists
4:06-4:24 Frequently used data science methods
4:24-5:21 How data scientists create value

We will try to provide a dynamic overview of the data science profession along with some key aspects such as:

✔️ Type of data used:
✔️ Activities performed on the job
✔️ Time allocation
✔️ Key skills
✔️ And frequently used data science methods

We’ll focus on how data scientists create value for companies and will explain how data science relates to AI, Machine Learning, and Deep Learning.

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Data Science is the convergence of computer science, mathematics, and business expertise and helps entrepreneurs predict, diagnose, and solve their problems. Luv Aggarwal, a Data Solution Engineer at IBM, goes through the basics and explains how the discipline deploys data mining, data cleaning, machine learning and a variety of advanced analytics to yield actionable insights that will provide a roadmap for growth.

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This AWS CloudFormation video tutorial shall teach you how to use AWS CloudFormation and why it is used. Towards the end, we will be learning how to create a template using a JSON script and also create a stack using the sample templates. This video tutorial is ideal for those want to become an AWS Certified Solutions Architect!
00:00:00 Agenda
00:00:53 Why AWS CloudFormation
00:06:08 AWS CloudFormation Components
00:27:48 Templates in CloudFormation
00:29:37 Stacks in CloudFormation
00:30:19 Direct Update
00:30:40 Update

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What is the AWS certification?

AWS is a top cloud service provider and the AWS certification is one of the leading IT certifications today. It consists of a wide range of expert insights, resources that help validate your technical skills and cloud expertise to improve your career and business.

Why learn AWS?

As AWS is one of the rapidly growing cloud services, it has over 1 million customers from 190 countries. Cloud skills have become critical to large enterprises, and thus the AWS certification provides enormous job opportunities with competitive salaries.

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