-
All Machine Learning Models Explained in 5 Minutes | Types of ML Models Basics
Confused about understanding machine learning models? Well, this video will help you grab the basics of each one of them. From what they are, to why they are used, and what purpose do they serve.
All Major Software Architecture Patterns Explained in 7 Minutes | Meaning, Design, Models & Examples
https://www.youtube.com/watch?v=ZTVAs9cNo30
7 Basic Machine Learning Concepts for Beginners
https://www.youtube.com/watch?v=4hlSztfaqoI
What is Deep Learning and How it Works | Deep Learning Explained
https://www.youtube.com/watch?v=DfRc3CeXLXw
Machine Learning Model Deployment Explained
https://www.youtube.com/watch?v=SHyFjJ-tIJE
What is Neural Network and How it Works | Neural Network Explained
https://www.youtube.com/watch?v=Ulx2CuMCyzI
What is Data Science Project Life Cycle Explained Ste...
published: 16 May 2020
-
What are Transformers (Machine Learning Model)?
Learn more about Transformers → http://ibm.biz/ML-Transformers
Learn more about AI → http://ibm.biz/more-about-ai
Check out IBM Watson → http://ibm.biz/more-about-watson
Transformers? In this case, we're talking about a machine learning model, and in this video Martin Keen explains what transformers are, what they're good for, and maybe ... what they're not so good at for.
Download a free AI ebook → http://ibm.biz/ai-ebook-free
Read about the Journey to AI → http://ibm.biz/ai-journey-blog
Get started for free on IBM Cloud → http://ibm.biz/Bdf7QA
Subscribe to see more videos like this in the future → http://ibm.biz/subscribe-now
#AI #Software #ITModernization
published: 11 Mar 2022
-
KÜNSTLICHE INTELLIGENZ vs. MACHINE LEARNING vs. DEEP LEARNING
Inhalt 📚
Künstliche #Intelligenz wird unsere #Gesellschaft verändern und ist schon heute aus unserem #Alltag kaum mehr wegzudenken: Seien es #Sprachassistenten, #Einparkhilfen oder der Umstand, dass dir #YouTube dieses #Video hier vorgeschlagen hat ... überall dort steckt mehr oder weniger #KI drin ... oder #AI ... oder neuronale Netze? Und was hat das eigentlich alles mit Deep Learning zu tun? Nun, diese #Buzzwords werden in letzter Zeit immer häufiger verwendet, um entweder sein eigenes #Produkt von der #Konkurrenz abzuheben oder um fachlich dünne #Bücher besser verkaufen zu können. Das Problem: Oft steckt in den entsprechenden Produkten gar nicht wirklich #KI drin und in den aggressiv beworbenen Büchern werden die Begriffe mehr schlecht als recht vermischt. In der #Praxis werden die Beg...
published: 26 Aug 2020
-
Transformers, explained: Understand the model behind GPT, BERT, and T5
Dale’s Blog → https://goo.gle/3xOeWoK
Classify text with BERT → https://goo.gle/3AUB431
Over the past five years, Transformers, a neural network architecture, have completely transformed state-of-the-art natural language processing. Want to translate text with machine learning? Curious how an ML model could write a poem or an op ed? Transformers can do it all. In this episode of Making with ML, Dale Markowitz explains what transformers are, how they work, and why they’re so impactful. Watch to learn how you can start using transformers in your app!
Chapters:
0:00 - Intro
0:51 - What are transformers?
3:18 - How do transformers work?
7:41 - How are transformers used?
8:35 - Getting started with transformers
Watch more episodes of Making with Machine Learning → https://goo.gle/2YysJRY
...
published: 18 Aug 2021
-
But what is a neural network? | Chapter 1, Deep learning
What are the neurons, why are there layers, and what is the math underlying it?
Help fund future projects: https://www.patreon.com/3blue1brown
Written/interactive form of this series: https://www.3blue1brown.com/topics/neural-networks
Additional funding for this project provided by Amplify Partners
Typo correction: At 14 minutes 45 seconds, the last index on the bias vector is n, when it's supposed to in fact be a k. Thanks for the sharp eyes that caught that!
For those who want to learn more, I highly recommend the book by Michael Nielsen introducing neural networks and deep learning: https://goo.gl/Zmczdy
There are two neat things about this book. First, it's available for free, so consider joining me in making a donation Nielsen's way if you get something out of it. And second, i...
published: 05 Oct 2017
-
Wie funktioniert eigentlich Machine Learning?
Künstliche Intelligenz verändert unser Leben. Alles, fast was wir online tun wird heute schon von "Machine Learning" beeinflusst. Und dennoch wissen viele von uns gar nicht, wie das eigentlich genau funktioniert. Wie lernt eine künstliche Intelligenz? Um diese Frage zu beantworten müssen wir zuerst klären, wie wir Menschen lernen.
Vielen Dank an ZEISS und im besonderen Dr. Jascha Ulrich für die Unterstützung bei diesem Video.
Für das ZDF durfte ich eine kleine Doku auf dem Kanal von Terra X produzieren: https://youtu.be/qzCD0ICPWEQ
Auf dem Kanal der Elektroindustrie mache ich regelmäßig Videos und erkläre zum Beispiel, wie Bitcoin funktioniert: https://youtu.be/9HO6Mz3jDmw
Natürlich bin ich weiter Sprecher auf dem Kanal Schlaumal: https://youtu.be/uvcleXH_GF8
Und ich war mal wieder z...
published: 01 Mar 2018
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Machine Learning #44 - Hidden Markov Modelle
In diesem Tutorial aufbauend auf den Markov Modellen von letztem Mal geht's heute um Hidden Markov Modelle.
❤❤❤ Früherer Zugang zu Tutorials, Abstimmungen, Live-Events und Downloads ❤❤❤
❤❤❤ https://www.patreon.com/user?u=5322110 ❤❤❤
❤❤❤ Keinen Bock auf Patreon? ❤❤❤
❤❤❤ https://www.paypal.me/TheMorpheus ❤❤❤
🌍 Website
🌍 https://the-morpheus.de
¯\_(ツ)_/¯ Tritt der Community bei ¯\_(ツ)_/¯
** https://the-morpheus.de/discord.html **
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( ͡° ͜ʖ ͡°) Mehr News? Mehr Code?
ℱ https://www.facebook.com/themorpheustutorials
🐦 https://twitter.com/TheMorpheusTuts
🐙 https://github.com/TheMorpheus407/Tutorials
Du bestellst bei Amazon? Bestell über mich, kostet dich null und du hilfst mir
»-(¯`·.·´¯)-» http://amzn.to/2slBSgH
Videowünsche?
🎁 https://docs.go...
published: 03 Mar 2017
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Diffusion models explained in 4-difficulty levels
In this video, we will take a close look at diffusion models. Diffusion models are being used in many domains but they are most famous for image generation. You might have seen diffusion models at work through Dall-e 2 and Imagen.
Let's look into how diffusion models learn and manage to create high-resolution, realistic images.
Check out the blog post for a more detailed look at diffusion models. https://www.assemblyai.com/blog/diffusion-models-for-machine-learning-introduction/
Get your Free Token for AssemblyAI Speech-To-Text API 👇https://www.assemblyai.com/?utm_source=youtube&utm_medium=referral&utm_campaign=yt_mis_30
▬▬▬▬▬▬▬▬▬▬▬▬ CONNECT ▬▬▬▬▬▬▬▬▬▬▬▬
🖥️ Website: https://www.assemblyai.com
🐦 Twitter: https://twitter.com/AssemblyAI
🦾 Discord: https://discord.gg/Cd8MyVJAXd
▶️ Subscri...
published: 17 Jun 2022
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Illustrated Guide to Transformers Neural Network: A step by step explanation
Transformers are the rage nowadays, but how do they work? This video demystifies the novel neural network architecture with step by step explanation and illustrations on how transformers work.
CORRECTIONS:
The sine and cosine functions are actually applied to the embedding dimensions and time steps!
⭐ Play and Experiment With the Latest AI Technologies at https://grandline.ai ⭐
Hugging Face Write with Transformers
https://transformer.huggingface.co/
published: 28 Apr 2020
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Attention mechanism: Overview
This video introduces you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. Attention is used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering.
Enroll in this course on Google Cloud Skills Boost → https://goo.gle/436ZFPR
View the Generative AI Learning path playlist → https://goo.gle/LearnGenAI
Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech
published: 05 Jun 2023
5:01
All Machine Learning Models Explained in 5 Minutes | Types of ML Models Basics
Confused about understanding machine learning models? Well, this video will help you grab the basics of each one of them. From what they are, to why they are us...
Confused about understanding machine learning models? Well, this video will help you grab the basics of each one of them. From what they are, to why they are used, and what purpose do they serve.
All Major Software Architecture Patterns Explained in 7 Minutes | Meaning, Design, Models & Examples
https://www.youtube.com/watch?v=ZTVAs9cNo30
7 Basic Machine Learning Concepts for Beginners
https://www.youtube.com/watch?v=4hlSztfaqoI
What is Deep Learning and How it Works | Deep Learning Explained
https://www.youtube.com/watch?v=DfRc3CeXLXw
Machine Learning Model Deployment Explained
https://www.youtube.com/watch?v=SHyFjJ-tIJE
What is Neural Network and How it Works | Neural Network Explained
https://www.youtube.com/watch?v=Ulx2CuMCyzI
What is Data Science Project Life Cycle Explained Step by Step
https://www.youtube.com/watch?v=vN5uZZ1h7VE
After watching this video, you'll be able to answer,
- How many machine learning models are there
- Some common machine learning models explained
- What is supervised learning
- What is unsupervised learning
- What is regression
- Types of ml models
- Common types of regression
- Common types of classification
- What is classification
- What are popular ML models explained
- What are the types of supervised learning
- What are the types of unsupervised learning
- Understanding the basics of machine learning models
- Learn machine learning models from scratch
- What are common machine learning models for beginners
- Understand machine learning models overview
- Whats are few ml models basics to grasp
Obviously, there is a ton of complexity if you dive into any particular model, but this should give you a fundamental understanding of how each machine learning model works!
Like my content? Be sure to smash that like button and hit Subscribe to get the latest updates!
Let's get social!
https://twitter.com/brandlitic
https://www.instagram.com/brandlitic
https://www.facebook.com/brandlitic
#WhiteboardProgramming #MachineLearning #MLmodels
https://wn.com/All_Machine_Learning_Models_Explained_In_5_Minutes_|_Types_Of_Ml_Models_Basics
Confused about understanding machine learning models? Well, this video will help you grab the basics of each one of them. From what they are, to why they are used, and what purpose do they serve.
All Major Software Architecture Patterns Explained in 7 Minutes | Meaning, Design, Models & Examples
https://www.youtube.com/watch?v=ZTVAs9cNo30
7 Basic Machine Learning Concepts for Beginners
https://www.youtube.com/watch?v=4hlSztfaqoI
What is Deep Learning and How it Works | Deep Learning Explained
https://www.youtube.com/watch?v=DfRc3CeXLXw
Machine Learning Model Deployment Explained
https://www.youtube.com/watch?v=SHyFjJ-tIJE
What is Neural Network and How it Works | Neural Network Explained
https://www.youtube.com/watch?v=Ulx2CuMCyzI
What is Data Science Project Life Cycle Explained Step by Step
https://www.youtube.com/watch?v=vN5uZZ1h7VE
After watching this video, you'll be able to answer,
- How many machine learning models are there
- Some common machine learning models explained
- What is supervised learning
- What is unsupervised learning
- What is regression
- Types of ml models
- Common types of regression
- Common types of classification
- What is classification
- What are popular ML models explained
- What are the types of supervised learning
- What are the types of unsupervised learning
- Understanding the basics of machine learning models
- Learn machine learning models from scratch
- What are common machine learning models for beginners
- Understand machine learning models overview
- Whats are few ml models basics to grasp
Obviously, there is a ton of complexity if you dive into any particular model, but this should give you a fundamental understanding of how each machine learning model works!
Like my content? Be sure to smash that like button and hit Subscribe to get the latest updates!
Let's get social!
https://twitter.com/brandlitic
https://www.instagram.com/brandlitic
https://www.facebook.com/brandlitic
#WhiteboardProgramming #MachineLearning #MLmodels
- published: 16 May 2020
- views: 1118197
5:50
What are Transformers (Machine Learning Model)?
Learn more about Transformers → http://ibm.biz/ML-Transformers
Learn more about AI → http://ibm.biz/more-about-ai
Check out IBM Watson → http://ibm.biz/more-abo...
Learn more about Transformers → http://ibm.biz/ML-Transformers
Learn more about AI → http://ibm.biz/more-about-ai
Check out IBM Watson → http://ibm.biz/more-about-watson
Transformers? In this case, we're talking about a machine learning model, and in this video Martin Keen explains what transformers are, what they're good for, and maybe ... what they're not so good at for.
Download a free AI ebook → http://ibm.biz/ai-ebook-free
Read about the Journey to AI → http://ibm.biz/ai-journey-blog
Get started for free on IBM Cloud → http://ibm.biz/Bdf7QA
Subscribe to see more videos like this in the future → http://ibm.biz/subscribe-now
#AI #Software #ITModernization
https://wn.com/What_Are_Transformers_(Machine_Learning_Model)
Learn more about Transformers → http://ibm.biz/ML-Transformers
Learn more about AI → http://ibm.biz/more-about-ai
Check out IBM Watson → http://ibm.biz/more-about-watson
Transformers? In this case, we're talking about a machine learning model, and in this video Martin Keen explains what transformers are, what they're good for, and maybe ... what they're not so good at for.
Download a free AI ebook → http://ibm.biz/ai-ebook-free
Read about the Journey to AI → http://ibm.biz/ai-journey-blog
Get started for free on IBM Cloud → http://ibm.biz/Bdf7QA
Subscribe to see more videos like this in the future → http://ibm.biz/subscribe-now
#AI #Software #ITModernization
- published: 11 Mar 2022
- views: 285158
8:28
KÜNSTLICHE INTELLIGENZ vs. MACHINE LEARNING vs. DEEP LEARNING
Inhalt 📚
Künstliche #Intelligenz wird unsere #Gesellschaft verändern und ist schon heute aus unserem #Alltag kaum mehr wegzudenken: Seien es #Sprachassistenten,...
Inhalt 📚
Künstliche #Intelligenz wird unsere #Gesellschaft verändern und ist schon heute aus unserem #Alltag kaum mehr wegzudenken: Seien es #Sprachassistenten, #Einparkhilfen oder der Umstand, dass dir #YouTube dieses #Video hier vorgeschlagen hat ... überall dort steckt mehr oder weniger #KI drin ... oder #AI ... oder neuronale Netze? Und was hat das eigentlich alles mit Deep Learning zu tun? Nun, diese #Buzzwords werden in letzter Zeit immer häufiger verwendet, um entweder sein eigenes #Produkt von der #Konkurrenz abzuheben oder um fachlich dünne #Bücher besser verkaufen zu können. Das Problem: Oft steckt in den entsprechenden Produkten gar nicht wirklich #KI drin und in den aggressiv beworbenen Büchern werden die Begriffe mehr schlecht als recht vermischt. In der #Praxis werden die Begriffe Machine Learning und #KI #synonym verwendet, um Supervised Learning zu bezeichnen. In diesem #Video möchte ich dir in einfachen Worten erklären, was tatsächlich hinter den #Buzzwords #KI bzw. #AI, Machine Learning Deep Learning und neuronalen Netzen steckt. Das versetzt dich außerdem in die Lage, #Dampfplauderer zukünftig auch als solche zu erkennen!
Einführung: 0:00
Was versteht man unter künstlicher Intelligenz (KI)? 0:56
Starke vs. schwache künstliche Intelligenz: 2:26
Wo entfaltet KI ihr Potenzial? 2:57
Was versteht man unter Machine Learning? 3:34
Supervised Learning: 4:09
Unsupervised Learning: 4:50
Reinforcement Learning: 5:35
Beispiele für Machine Learning: 6:17
Was versteht man unter Deep Learning? 6:33
Neuronale Netze (Neuronen, Synapsen, Layer) 6:57
Zusammenfassung: 8:02
ENDE: 8:21
EQUIPMENT(*)
🎤 Mikrofon https://amzn.to/3N0CHCL
✂️ Schnittprogramm https://amzn.to/3CZ217J
💻 Mein Laptop https://amzn.to/3ikMd5V
🖥️ Bildschirm https://amzn.to/3ig3yN5
SUPPORT
► Patreon https://patreon.com/florian_dalwigk
► PayPal
► Unterstütze mich durch einen Kauf auf Amazon. Für dich entstehen keine Mehrkosten! (*) https://amzn.to/3LgyglY
SOCIAL MEDIA
💬 Discord: https://discord.gg/X7QU7GXC2u
💡 Website: https://www.florian-dalwigk.de
📱 TikTok: https://www.tiktok.com/@florian.dalwigk
🤳 Instagram: https://www.instagram.com/florian.dalwigk
🐦 Twitter: https://twitter.com/florian_dalwigk
📧 E-Mail: mailto:info@florian-dalwigk.de
📼 Video zum Unterschied zwischen schwacher und starker KI [FOLGT]
📼 Video zum Quantenzufallszahlengenerator (#QRNG) https://www.youtube.com/watch?v=j5Zxu0b2TN4
🔗 Studie von McKinsey https://www.mckinsey.com/~/media/McKinsey/Industries/Semiconductors/Our%20Insights/Smartening%20up%20with%20artificial%20intelligence/Smartening-up-with-artificial-intelligence.ashx
(*) Bei den Amazon-Links (https.//amzn.to/???????) handelt es sich um Affiliate-Links. Wenn du etwas über diesen Link kaufst, bekomme ich eine kleine Provision. Der Preis ändert sich nicht, wenn du über diesen Link einkaufst. Vielen Dank für deine Unterstützung.
https://wn.com/Künstliche_Intelligenz_Vs._Machine_Learning_Vs._Deep_Learning
Inhalt 📚
Künstliche #Intelligenz wird unsere #Gesellschaft verändern und ist schon heute aus unserem #Alltag kaum mehr wegzudenken: Seien es #Sprachassistenten, #Einparkhilfen oder der Umstand, dass dir #YouTube dieses #Video hier vorgeschlagen hat ... überall dort steckt mehr oder weniger #KI drin ... oder #AI ... oder neuronale Netze? Und was hat das eigentlich alles mit Deep Learning zu tun? Nun, diese #Buzzwords werden in letzter Zeit immer häufiger verwendet, um entweder sein eigenes #Produkt von der #Konkurrenz abzuheben oder um fachlich dünne #Bücher besser verkaufen zu können. Das Problem: Oft steckt in den entsprechenden Produkten gar nicht wirklich #KI drin und in den aggressiv beworbenen Büchern werden die Begriffe mehr schlecht als recht vermischt. In der #Praxis werden die Begriffe Machine Learning und #KI #synonym verwendet, um Supervised Learning zu bezeichnen. In diesem #Video möchte ich dir in einfachen Worten erklären, was tatsächlich hinter den #Buzzwords #KI bzw. #AI, Machine Learning Deep Learning und neuronalen Netzen steckt. Das versetzt dich außerdem in die Lage, #Dampfplauderer zukünftig auch als solche zu erkennen!
Einführung: 0:00
Was versteht man unter künstlicher Intelligenz (KI)? 0:56
Starke vs. schwache künstliche Intelligenz: 2:26
Wo entfaltet KI ihr Potenzial? 2:57
Was versteht man unter Machine Learning? 3:34
Supervised Learning: 4:09
Unsupervised Learning: 4:50
Reinforcement Learning: 5:35
Beispiele für Machine Learning: 6:17
Was versteht man unter Deep Learning? 6:33
Neuronale Netze (Neuronen, Synapsen, Layer) 6:57
Zusammenfassung: 8:02
ENDE: 8:21
EQUIPMENT(*)
🎤 Mikrofon https://amzn.to/3N0CHCL
✂️ Schnittprogramm https://amzn.to/3CZ217J
💻 Mein Laptop https://amzn.to/3ikMd5V
🖥️ Bildschirm https://amzn.to/3ig3yN5
SUPPORT
► Patreon https://patreon.com/florian_dalwigk
► PayPal
► Unterstütze mich durch einen Kauf auf Amazon. Für dich entstehen keine Mehrkosten! (*) https://amzn.to/3LgyglY
SOCIAL MEDIA
💬 Discord: https://discord.gg/X7QU7GXC2u
💡 Website: https://www.florian-dalwigk.de
📱 TikTok: https://www.tiktok.com/@florian.dalwigk
🤳 Instagram: https://www.instagram.com/florian.dalwigk
🐦 Twitter: https://twitter.com/florian_dalwigk
📧 E-Mail: mailto:info@florian-dalwigk.de
📼 Video zum Unterschied zwischen schwacher und starker KI [FOLGT]
📼 Video zum Quantenzufallszahlengenerator (#QRNG) https://www.youtube.com/watch?v=j5Zxu0b2TN4
🔗 Studie von McKinsey https://www.mckinsey.com/~/media/McKinsey/Industries/Semiconductors/Our%20Insights/Smartening%20up%20with%20artificial%20intelligence/Smartening-up-with-artificial-intelligence.ashx
(*) Bei den Amazon-Links (https.//amzn.to/???????) handelt es sich um Affiliate-Links. Wenn du etwas über diesen Link kaufst, bekomme ich eine kleine Provision. Der Preis ändert sich nicht, wenn du über diesen Link einkaufst. Vielen Dank für deine Unterstützung.
- published: 26 Aug 2020
- views: 135347
9:11
Transformers, explained: Understand the model behind GPT, BERT, and T5
Dale’s Blog → https://goo.gle/3xOeWoK
Classify text with BERT → https://goo.gle/3AUB431
Over the past five years, Transformers, a neural network architecture, ...
Dale’s Blog → https://goo.gle/3xOeWoK
Classify text with BERT → https://goo.gle/3AUB431
Over the past five years, Transformers, a neural network architecture, have completely transformed state-of-the-art natural language processing. Want to translate text with machine learning? Curious how an ML model could write a poem or an op ed? Transformers can do it all. In this episode of Making with ML, Dale Markowitz explains what transformers are, how they work, and why they’re so impactful. Watch to learn how you can start using transformers in your app!
Chapters:
0:00 - Intro
0:51 - What are transformers?
3:18 - How do transformers work?
7:41 - How are transformers used?
8:35 - Getting started with transformers
Watch more episodes of Making with Machine Learning → https://goo.gle/2YysJRY
Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech
#MakingwithMachineLearning #MakingwithML
product: Cloud - General; fullname: Dale Markowitz; re_ty: Publish;
https://wn.com/Transformers,_Explained_Understand_The_Model_Behind_Gpt,_Bert,_And_T5
Dale’s Blog → https://goo.gle/3xOeWoK
Classify text with BERT → https://goo.gle/3AUB431
Over the past five years, Transformers, a neural network architecture, have completely transformed state-of-the-art natural language processing. Want to translate text with machine learning? Curious how an ML model could write a poem or an op ed? Transformers can do it all. In this episode of Making with ML, Dale Markowitz explains what transformers are, how they work, and why they’re so impactful. Watch to learn how you can start using transformers in your app!
Chapters:
0:00 - Intro
0:51 - What are transformers?
3:18 - How do transformers work?
7:41 - How are transformers used?
8:35 - Getting started with transformers
Watch more episodes of Making with Machine Learning → https://goo.gle/2YysJRY
Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech
#MakingwithMachineLearning #MakingwithML
product: Cloud - General; fullname: Dale Markowitz; re_ty: Publish;
- published: 18 Aug 2021
- views: 817723
18:40
But what is a neural network? | Chapter 1, Deep learning
What are the neurons, why are there layers, and what is the math underlying it?
Help fund future projects: https://www.patreon.com/3blue1brown
Written/interacti...
What are the neurons, why are there layers, and what is the math underlying it?
Help fund future projects: https://www.patreon.com/3blue1brown
Written/interactive form of this series: https://www.3blue1brown.com/topics/neural-networks
Additional funding for this project provided by Amplify Partners
Typo correction: At 14 minutes 45 seconds, the last index on the bias vector is n, when it's supposed to in fact be a k. Thanks for the sharp eyes that caught that!
For those who want to learn more, I highly recommend the book by Michael Nielsen introducing neural networks and deep learning: https://goo.gl/Zmczdy
There are two neat things about this book. First, it's available for free, so consider joining me in making a donation Nielsen's way if you get something out of it. And second, it's centered around walking through some code and data which you can download yourself, and which covers the same example that I introduce in this video. Yay for active learning!
https://github.com/mnielsen/neural-networks-and-deep-learning
I also highly recommend Chris Olah's blog: http://colah.github.io/
For more videos, Welch Labs also has some great series on machine learning:
https://youtu.be/i8D90DkCLhI
https://youtu.be/bxe2T-V8XRs
For those of you looking to go *even* deeper, check out the text "Deep Learning" by Goodfellow, Bengio, and Courville.
Also, the publication Distill is just utterly beautiful: https://distill.pub/
Lion photo by Kevin Pluck
Thanks to these viewers for their contributions to translations
German: @fpgro
Hebrew: Omer Tuchfeld
Hungarian: Máté Kaszap
Italian: @teobucci, Teo Bucci
-----------------
Timeline:
0:00 - Introduction example
1:07 - Series preview
2:42 - What are neurons?
3:35 - Introducing layers
5:31 - Why layers?
8:38 - Edge detection example
11:34 - Counting weights and biases
12:30 - How learning relates
13:26 - Notation and linear algebra
15:17 - Recap
16:27 - Some final words
17:03 - ReLU vs Sigmoid
Correction 14:45 - The final index on the bias vector should be "k"
------------------
Animations largely made using manim, a scrappy open source python library. https://github.com/3b1b/manim
If you want to check it out, I feel compelled to warn you that it's not the most well-documented tool, and has many other quirks you might expect in a library someone wrote with only their own use in mind.
Music by Vincent Rubinetti.
Download the music on Bandcamp:
https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown
Stream the music on Spotify:
https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u
If you want to contribute translated subtitles or to help review those that have already been made by others and need approval, you can click the gear icon in the video and go to subtitles/cc, then "add subtitles/cc". I really appreciate those who do this, as it helps make the lessons accessible to more people.
------------------
3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you're into that).
If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended
Various social media stuffs:
Website: https://www.3blue1brown.com
Twitter: https://twitter.com/3Blue1Brown
Patreon: https://patreon.com/3blue1brown
Facebook: https://www.facebook.com/3blue1brown
Reddit: https://www.reddit.com/r/3Blue1Brown
https://wn.com/But_What_Is_A_Neural_Network_|_Chapter_1,_Deep_Learning
What are the neurons, why are there layers, and what is the math underlying it?
Help fund future projects: https://www.patreon.com/3blue1brown
Written/interactive form of this series: https://www.3blue1brown.com/topics/neural-networks
Additional funding for this project provided by Amplify Partners
Typo correction: At 14 minutes 45 seconds, the last index on the bias vector is n, when it's supposed to in fact be a k. Thanks for the sharp eyes that caught that!
For those who want to learn more, I highly recommend the book by Michael Nielsen introducing neural networks and deep learning: https://goo.gl/Zmczdy
There are two neat things about this book. First, it's available for free, so consider joining me in making a donation Nielsen's way if you get something out of it. And second, it's centered around walking through some code and data which you can download yourself, and which covers the same example that I introduce in this video. Yay for active learning!
https://github.com/mnielsen/neural-networks-and-deep-learning
I also highly recommend Chris Olah's blog: http://colah.github.io/
For more videos, Welch Labs also has some great series on machine learning:
https://youtu.be/i8D90DkCLhI
https://youtu.be/bxe2T-V8XRs
For those of you looking to go *even* deeper, check out the text "Deep Learning" by Goodfellow, Bengio, and Courville.
Also, the publication Distill is just utterly beautiful: https://distill.pub/
Lion photo by Kevin Pluck
Thanks to these viewers for their contributions to translations
German: @fpgro
Hebrew: Omer Tuchfeld
Hungarian: Máté Kaszap
Italian: @teobucci, Teo Bucci
-----------------
Timeline:
0:00 - Introduction example
1:07 - Series preview
2:42 - What are neurons?
3:35 - Introducing layers
5:31 - Why layers?
8:38 - Edge detection example
11:34 - Counting weights and biases
12:30 - How learning relates
13:26 - Notation and linear algebra
15:17 - Recap
16:27 - Some final words
17:03 - ReLU vs Sigmoid
Correction 14:45 - The final index on the bias vector should be "k"
------------------
Animations largely made using manim, a scrappy open source python library. https://github.com/3b1b/manim
If you want to check it out, I feel compelled to warn you that it's not the most well-documented tool, and has many other quirks you might expect in a library someone wrote with only their own use in mind.
Music by Vincent Rubinetti.
Download the music on Bandcamp:
https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown
Stream the music on Spotify:
https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u
If you want to contribute translated subtitles or to help review those that have already been made by others and need approval, you can click the gear icon in the video and go to subtitles/cc, then "add subtitles/cc". I really appreciate those who do this, as it helps make the lessons accessible to more people.
------------------
3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you're into that).
If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended
Various social media stuffs:
Website: https://www.3blue1brown.com
Twitter: https://twitter.com/3Blue1Brown
Patreon: https://patreon.com/3blue1brown
Facebook: https://www.facebook.com/3blue1brown
Reddit: https://www.reddit.com/r/3Blue1Brown
- published: 05 Oct 2017
- views: 15601446
8:11
Wie funktioniert eigentlich Machine Learning?
Künstliche Intelligenz verändert unser Leben. Alles, fast was wir online tun wird heute schon von "Machine Learning" beeinflusst. Und dennoch wissen viele von u...
Künstliche Intelligenz verändert unser Leben. Alles, fast was wir online tun wird heute schon von "Machine Learning" beeinflusst. Und dennoch wissen viele von uns gar nicht, wie das eigentlich genau funktioniert. Wie lernt eine künstliche Intelligenz? Um diese Frage zu beantworten müssen wir zuerst klären, wie wir Menschen lernen.
Vielen Dank an ZEISS und im besonderen Dr. Jascha Ulrich für die Unterstützung bei diesem Video.
Für das ZDF durfte ich eine kleine Doku auf dem Kanal von Terra X produzieren: https://youtu.be/qzCD0ICPWEQ
Auf dem Kanal der Elektroindustrie mache ich regelmäßig Videos und erkläre zum Beispiel, wie Bitcoin funktioniert: https://youtu.be/9HO6Mz3jDmw
Natürlich bin ich weiter Sprecher auf dem Kanal Schlaumal: https://youtu.be/uvcleXH_GF8
Und ich war mal wieder zu Besuch bei Phil's Physics: https://youtu.be/47Mo1puuzsg
Patreon: https://www.patreon.com/DoktorWhatson
Twitter: http://www.twitter.com/DoktorWhatson
Instagram: http://instagram.com/DoktorWhatson
Facebook: http://www.facebook.com/DoktorWhatson
Musik:
Novah – Sea of Clouds
https://www.youtube.com/user/NovahMedia
https://soundcloud.com/novahofficial
https://wn.com/Wie_Funktioniert_Eigentlich_Machine_Learning
Künstliche Intelligenz verändert unser Leben. Alles, fast was wir online tun wird heute schon von "Machine Learning" beeinflusst. Und dennoch wissen viele von uns gar nicht, wie das eigentlich genau funktioniert. Wie lernt eine künstliche Intelligenz? Um diese Frage zu beantworten müssen wir zuerst klären, wie wir Menschen lernen.
Vielen Dank an ZEISS und im besonderen Dr. Jascha Ulrich für die Unterstützung bei diesem Video.
Für das ZDF durfte ich eine kleine Doku auf dem Kanal von Terra X produzieren: https://youtu.be/qzCD0ICPWEQ
Auf dem Kanal der Elektroindustrie mache ich regelmäßig Videos und erkläre zum Beispiel, wie Bitcoin funktioniert: https://youtu.be/9HO6Mz3jDmw
Natürlich bin ich weiter Sprecher auf dem Kanal Schlaumal: https://youtu.be/uvcleXH_GF8
Und ich war mal wieder zu Besuch bei Phil's Physics: https://youtu.be/47Mo1puuzsg
Patreon: https://www.patreon.com/DoktorWhatson
Twitter: http://www.twitter.com/DoktorWhatson
Instagram: http://instagram.com/DoktorWhatson
Facebook: http://www.facebook.com/DoktorWhatson
Musik:
Novah – Sea of Clouds
https://www.youtube.com/user/NovahMedia
https://soundcloud.com/novahofficial
- published: 01 Mar 2018
- views: 216210
5:28
Machine Learning #44 - Hidden Markov Modelle
In diesem Tutorial aufbauend auf den Markov Modellen von letztem Mal geht's heute um Hidden Markov Modelle.
❤❤❤ Früherer Zugang zu Tutorials, Abstimmungen, Live...
In diesem Tutorial aufbauend auf den Markov Modellen von letztem Mal geht's heute um Hidden Markov Modelle.
❤❤❤ Früherer Zugang zu Tutorials, Abstimmungen, Live-Events und Downloads ❤❤❤
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🌍 Website
🌍 https://the-morpheus.de
¯\_(ツ)_/¯ Tritt der Community bei ¯\_(ツ)_/¯
** https://the-morpheus.de/discord.html **
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Du bestellst bei Amazon? Bestell über mich, kostet dich null und du hilfst mir
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Videowünsche?
🎁 https://docs.google.com/spreadsheets/d/1YPv8fFJOMRyyhUggK8phrx01OoYXZEovwDLdU4D4nkk/edit#gid=0
Fragen? Feedback? Schreib mir!
✉ https://www.patreon.com/user?u=5322110
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oder schreib einfach ein Kommentar :)
https://wn.com/Machine_Learning_44_Hidden_Markov_Modelle
In diesem Tutorial aufbauend auf den Markov Modellen von letztem Mal geht's heute um Hidden Markov Modelle.
❤❤❤ Früherer Zugang zu Tutorials, Abstimmungen, Live-Events und Downloads ❤❤❤
❤❤❤ https://www.patreon.com/user?u=5322110 ❤❤❤
❤❤❤ Keinen Bock auf Patreon? ❤❤❤
❤❤❤ https://www.paypal.me/TheMorpheus ❤❤❤
🌍 Website
🌍 https://the-morpheus.de
¯\_(ツ)_/¯ Tritt der Community bei ¯\_(ツ)_/¯
** https://the-morpheus.de/discord.html **
** https://www.reddit.com/r/TheMorpheusTuts/ **
( ͡° ͜ʖ ͡°) Mehr News? Mehr Code?
ℱ https://www.facebook.com/themorpheustutorials
🐦 https://twitter.com/TheMorpheusTuts
🐙 https://github.com/TheMorpheus407/Tutorials
Du bestellst bei Amazon? Bestell über mich, kostet dich null und du hilfst mir
»-(¯`·.·´¯)-» http://amzn.to/2slBSgH
Videowünsche?
🎁 https://docs.google.com/spreadsheets/d/1YPv8fFJOMRyyhUggK8phrx01OoYXZEovwDLdU4D4nkk/edit#gid=0
Fragen? Feedback? Schreib mir!
✉ https://www.patreon.com/user?u=5322110
✉ https://www.facebook.com/themorpheustutorials
✉ https://the-morpheus.de/discord.html
oder schreib einfach ein Kommentar :)
- published: 03 Mar 2017
- views: 10058
7:08
Diffusion models explained in 4-difficulty levels
In this video, we will take a close look at diffusion models. Diffusion models are being used in many domains but they are most famous for image generation. You...
In this video, we will take a close look at diffusion models. Diffusion models are being used in many domains but they are most famous for image generation. You might have seen diffusion models at work through Dall-e 2 and Imagen.
Let's look into how diffusion models learn and manage to create high-resolution, realistic images.
Check out the blog post for a more detailed look at diffusion models. https://www.assemblyai.com/blog/diffusion-models-for-machine-learning-introduction/
Get your Free Token for AssemblyAI Speech-To-Text API 👇https://www.assemblyai.com/?utm_source=youtube&utm_medium=referral&utm_campaign=yt_mis_30
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#MachineLearning #DeepLearning
https://wn.com/Diffusion_Models_Explained_In_4_Difficulty_Levels
In this video, we will take a close look at diffusion models. Diffusion models are being used in many domains but they are most famous for image generation. You might have seen diffusion models at work through Dall-e 2 and Imagen.
Let's look into how diffusion models learn and manage to create high-resolution, realistic images.
Check out the blog post for a more detailed look at diffusion models. https://www.assemblyai.com/blog/diffusion-models-for-machine-learning-introduction/
Get your Free Token for AssemblyAI Speech-To-Text API 👇https://www.assemblyai.com/?utm_source=youtube&utm_medium=referral&utm_campaign=yt_mis_30
▬▬▬▬▬▬▬▬▬▬▬▬ CONNECT ▬▬▬▬▬▬▬▬▬▬▬▬
🖥️ Website: https://www.assemblyai.com
🐦 Twitter: https://twitter.com/AssemblyAI
🦾 Discord: https://discord.gg/Cd8MyVJAXd
▶️ Subscribe: https://www.youtube.com/c/AssemblyAI?sub_confirmation=1
🔥 We're hiring! Check our open roles: https://www.assemblyai.com/careers
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#MachineLearning #DeepLearning
- published: 17 Jun 2022
- views: 99372
15:01
Illustrated Guide to Transformers Neural Network: A step by step explanation
Transformers are the rage nowadays, but how do they work? This video demystifies the novel neural network architecture with step by step explanation and illustr...
Transformers are the rage nowadays, but how do they work? This video demystifies the novel neural network architecture with step by step explanation and illustrations on how transformers work.
CORRECTIONS:
The sine and cosine functions are actually applied to the embedding dimensions and time steps!
⭐ Play and Experiment With the Latest AI Technologies at https://grandline.ai ⭐
Hugging Face Write with Transformers
https://transformer.huggingface.co/
https://wn.com/Illustrated_Guide_To_Transformers_Neural_Network_A_Step_By_Step_Explanation
Transformers are the rage nowadays, but how do they work? This video demystifies the novel neural network architecture with step by step explanation and illustrations on how transformers work.
CORRECTIONS:
The sine and cosine functions are actually applied to the embedding dimensions and time steps!
⭐ Play and Experiment With the Latest AI Technologies at https://grandline.ai ⭐
Hugging Face Write with Transformers
https://transformer.huggingface.co/
- published: 28 Apr 2020
- views: 850311
5:34
Attention mechanism: Overview
This video introduces you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. Attentio...
This video introduces you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. Attention is used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering.
Enroll in this course on Google Cloud Skills Boost → https://goo.gle/436ZFPR
View the Generative AI Learning path playlist → https://goo.gle/LearnGenAI
Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech
https://wn.com/Attention_Mechanism_Overview
This video introduces you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. Attention is used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering.
Enroll in this course on Google Cloud Skills Boost → https://goo.gle/436ZFPR
View the Generative AI Learning path playlist → https://goo.gle/LearnGenAI
Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech
- published: 05 Jun 2023
- views: 83772