A sigmoid function is a mathematical function having an "S" shape (sigmoid curve). Often, sigmoid function refers to the special case of the logistic function shown in the first figure and defined by the formula
In this video we discuss the sigmoid function.
The sigmoid function plays an important role in the field of machine learning and is considered as one of the most widely used so-called activation functions.
More specifically, in the context of logistic regression, the sigmoid is used to predict the outcome of binary classification problems.
#sigmoid #machinelearning #logisitcregression #binaryclassification
published: 19 Jun 2020
Sigmoid function Explained in simplest way
Sigmoid is used as an activation function in lot of machine learning problem,In this video I have tried to explain sigmoid function with very simple example.
A sigmoid function can convert any real value sample to a probability range of 0 to 1 this property of sigmoid help's to utilize it logistic regression problems.
In the further session we have explained logic regression here is the link for the video..
https://www.youtube.com/watch?v=6Q2SXLuv-4E
For a complete index of all the machine learning videos, check out:
https://www.youtube.com/channel/UCoB1kaaQrQEkB-ud2QxmgUQ/videos
published: 29 Jul 2019
Why do we use "e" in the Sigmoid?
Why do we use the mathematical constant "e" in the sigmoid function?
My Patreon : https://www.patreon.com/user?u=49277905
Sigmoid Video : https://www.youtube.com/watch?v=Aj7O9qRNJPY
Visuals Created with Excalidraw : https://excalidraw.com/
published: 26 Jun 2023
The Sigmoid : Data Science Basics
All about the all-powerful SIGMOID function in machine learning!
published: 25 May 2020
Why Do We Use the Sigmoid Function for Binary Classification?
This video explains why we use the sigmoid function in neural networks for machine learning, especially for binary classification. We consider both the practical side of making sure we get a consistent gradient from the standard categorical loss function, as well as making sure the equation is easily computable. We also look at the statistical side by giving an interpretation for what the logit values represent (the values passed into the sigmoid function), and how they can be thought of as normally distributed values with their means shifted one way or the other depending on which class they are for.
My other video, "Derivative of Sigmoid and Softmax Explained Visually":
📼 https://youtu.be/gRr2Q97XS2g
The Desmos graph of the sigmoid function:
📈https://www.desmos.com/calculator/hjc4peyxm...
published: 20 Feb 2020
MFML 111 - What are all those sigmoid functions for?
Wondering what all those sigmoid functions are for and why you see them all over machine learning? The answer is simple and it has to do with something you'd learn on day 1 of an economics 101 class...
Be sure to watch this episode along with episode 110 so it makes more sense. Also, do check out the rest of the MFML course playlist here: http://bit.ly/machinefriend
If you prefer to learn in bulk, you can get access to longer chunks of the course by signing up for the newsletter at http://decision.substack.com
Don't forget to hit subscribe+notify! If you found this useful or enjoyable, the best way to say thank you is by sharing it.
published: 28 Apr 2022
3. Sigmoid Activation Function Solved Example | Soft Computing | Machine Learning ANN Mahesh Huddar
3. Sigmoid Activation Function Solved Example | Soft Computing | Artificial Neural Network | Machine Learning | Data Mining Mahesh Huddar
The following concepts are discussed:
______________________________
How to find the output of the neuron Y using
the binary sigmoid activation function and
the bipolar sigmoid activation function.
Sigmoid activation function solved example,
Sigmoid activation function Numerical example,
Sigmoid activation function example
Sigmoid function solved example,
Sigmoid function numerical example,
Sigmoid function example
********************************
1. Blog / Website: https://www.vtupulse.com/
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3. Follow us on Instagram: https://www.instagram.com/vtupulse/
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published: 09 Oct 2022
Sigmoid Activation Function - Deep Learning Dictionary
What is the sigmoid activation function used in artificial neural networks?
👉 To gain early access to the full Deep Learning Dictionary course, register at:
🔗 https://deeplizard.com/course/ddcpailzrd
👉 For more in depth lessons, check out the Deep Learning Fundamentals course:
🔗 https://deeplizard.com/course/dlcpailzrd
🕒🦎 VIDEO SECTIONS 🦎🕒
00:00 Welcome to DEEPLIZARD - Go to deeplizard.com for learning resources
00:10 Sigmoid Activation Function
02:21 Collective Intelligence and the DEEPLIZARD HIVEMIND
💥🦎 DEEPLIZARD COMMUNITY RESOURCES 🦎💥
👋 Hey, we're Chris and Mandy, the creators of deeplizard!
👉 Check out the website for more learning material:
🔗 https://deeplizard.com
💻 ENROLL TO GET DOWNLOAD ACCESS TO CODE FILES
🔗 https://deeplizard.com/resources
🧠 Support collective intellig...
published: 11 Jul 2022
[Intuitive Deep Learning] 3.5 Hands-on examples:Shallow to deep nets with backprop and batching
#IntuitiveDeepLearning #SimpleMathematicsOfDL #linearalgebra
The ANNOTATED summary of this lecture 3.5 is available at:
https://drive.google.com/file/d/1WgiBYf6pYsgZLCDZBao69FWYHXzwBssj/view?usp=sharing
In this DL map video we briefly cover the following topics:
1. How a simple linear 1-1-1 neural model operates with/out bias
2. How a simple non-linear 1-1-1 neural model operates with/out bias
3. Going deeper and adding more hidden units
4. Loss differentiation
5. Batching
📚🔗 The ANNOTATED summary map of the DL linear algebra of the second lecture videos 3.1 to 3.4 can be found at: https://drive.google.com/file/d/1pgr7uEepG3VTHalo4CyyO9yJtS07xp81/view?usp=sharing
📚🔗 The CLEAN summary map of the DL linear algebra of the second lecture videos 3.1 to 3.4 can be found at: https://drive....
published: 28 Dec 2023
Sigmoid
Watch on Udacity: https://www.udacity.com/course/viewer#!/c-ud262/l-315142919/m-432088680
Check out the full Advanced Operating Systems course for free at: https://www.udacity.com/course/ud262
Georgia Tech online Master's program: https://www.udacity.com/georgia-tech
In this video we discuss the sigmoid function.
The sigmoid function plays an important role in the field of machine learning and is considered as one of the mo...
In this video we discuss the sigmoid function.
The sigmoid function plays an important role in the field of machine learning and is considered as one of the most widely used so-called activation functions.
More specifically, in the context of logistic regression, the sigmoid is used to predict the outcome of binary classification problems.
#sigmoid #machinelearning #logisitcregression #binaryclassification
In this video we discuss the sigmoid function.
The sigmoid function plays an important role in the field of machine learning and is considered as one of the most widely used so-called activation functions.
More specifically, in the context of logistic regression, the sigmoid is used to predict the outcome of binary classification problems.
#sigmoid #machinelearning #logisitcregression #binaryclassification
Sigmoid is used as an activation function in lot of machine learning problem,In this video I have tried to explain sigmoid function with very simple example.
A...
Sigmoid is used as an activation function in lot of machine learning problem,In this video I have tried to explain sigmoid function with very simple example.
A sigmoid function can convert any real value sample to a probability range of 0 to 1 this property of sigmoid help's to utilize it logistic regression problems.
In the further session we have explained logic regression here is the link for the video..
https://www.youtube.com/watch?v=6Q2SXLuv-4E
For a complete index of all the machine learning videos, check out:
https://www.youtube.com/channel/UCoB1kaaQrQEkB-ud2QxmgUQ/videos
Sigmoid is used as an activation function in lot of machine learning problem,In this video I have tried to explain sigmoid function with very simple example.
A sigmoid function can convert any real value sample to a probability range of 0 to 1 this property of sigmoid help's to utilize it logistic regression problems.
In the further session we have explained logic regression here is the link for the video..
https://www.youtube.com/watch?v=6Q2SXLuv-4E
For a complete index of all the machine learning videos, check out:
https://www.youtube.com/channel/UCoB1kaaQrQEkB-ud2QxmgUQ/videos
Why do we use the mathematical constant "e" in the sigmoid function?
My Patreon : https://www.patreon.com/user?u=49277905
Sigmoid Video : https://www.youtube....
Why do we use the mathematical constant "e" in the sigmoid function?
My Patreon : https://www.patreon.com/user?u=49277905
Sigmoid Video : https://www.youtube.com/watch?v=Aj7O9qRNJPY
Visuals Created with Excalidraw : https://excalidraw.com/
Why do we use the mathematical constant "e" in the sigmoid function?
My Patreon : https://www.patreon.com/user?u=49277905
Sigmoid Video : https://www.youtube.com/watch?v=Aj7O9qRNJPY
Visuals Created with Excalidraw : https://excalidraw.com/
This video explains why we use the sigmoid function in neural networks for machine learning, especially for binary classification. We consider both the practica...
This video explains why we use the sigmoid function in neural networks for machine learning, especially for binary classification. We consider both the practical side of making sure we get a consistent gradient from the standard categorical loss function, as well as making sure the equation is easily computable. We also look at the statistical side by giving an interpretation for what the logit values represent (the values passed into the sigmoid function), and how they can be thought of as normally distributed values with their means shifted one way or the other depending on which class they are for.
My other video, "Derivative of Sigmoid and Softmax Explained Visually":
📼 https://youtu.be/gRr2Q97XS2g
The Desmos graph of the sigmoid function:
📈https://www.desmos.com/calculator/hjc4peyxmc
Connect with me:
🐦 Twitter - https://twitter.com/elliotwaite
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→ https://soundcloud.com/ohthatkazuki
→ https://open.spotify.com/artist/5d07MpiIaNmmEMTq79KAga
→ https://www.youtube.com/user/OfficialKazuki
This video explains why we use the sigmoid function in neural networks for machine learning, especially for binary classification. We consider both the practical side of making sure we get a consistent gradient from the standard categorical loss function, as well as making sure the equation is easily computable. We also look at the statistical side by giving an interpretation for what the logit values represent (the values passed into the sigmoid function), and how they can be thought of as normally distributed values with their means shifted one way or the other depending on which class they are for.
My other video, "Derivative of Sigmoid and Softmax Explained Visually":
📼 https://youtu.be/gRr2Q97XS2g
The Desmos graph of the sigmoid function:
📈https://www.desmos.com/calculator/hjc4peyxmc
Connect with me:
🐦 Twitter - https://twitter.com/elliotwaite
📷 Instagram - https://www.instagram.com/elliotwaite
👱 Facebook - https://www.facebook.com/elliotwaite
💼 LinkedIn - https://www.linkedin.com/in/elliotwaite
Join our Discord community:
💬 https://discord.gg/cdQhRgw
🎵 Kazukii - Return
→ https://soundcloud.com/ohthatkazuki
→ https://open.spotify.com/artist/5d07MpiIaNmmEMTq79KAga
→ https://www.youtube.com/user/OfficialKazuki
Wondering what all those sigmoid functions are for and why you see them all over machine learning? The answer is simple and it has to do with something you'd le...
Wondering what all those sigmoid functions are for and why you see them all over machine learning? The answer is simple and it has to do with something you'd learn on day 1 of an economics 101 class...
Be sure to watch this episode along with episode 110 so it makes more sense. Also, do check out the rest of the MFML course playlist here: http://bit.ly/machinefriend
If you prefer to learn in bulk, you can get access to longer chunks of the course by signing up for the newsletter at http://decision.substack.com
Don't forget to hit subscribe+notify! If you found this useful or enjoyable, the best way to say thank you is by sharing it.
Wondering what all those sigmoid functions are for and why you see them all over machine learning? The answer is simple and it has to do with something you'd learn on day 1 of an economics 101 class...
Be sure to watch this episode along with episode 110 so it makes more sense. Also, do check out the rest of the MFML course playlist here: http://bit.ly/machinefriend
If you prefer to learn in bulk, you can get access to longer chunks of the course by signing up for the newsletter at http://decision.substack.com
Don't forget to hit subscribe+notify! If you found this useful or enjoyable, the best way to say thank you is by sharing it.
3. Sigmoid Activation Function Solved Example | Soft Computing | Artificial Neural Network | Machine Learning | Data Mining Mahesh Huddar
The following concep...
3. Sigmoid Activation Function Solved Example | Soft Computing | Artificial Neural Network | Machine Learning | Data Mining Mahesh Huddar
The following concepts are discussed:
______________________________
How to find the output of the neuron Y using
the binary sigmoid activation function and
the bipolar sigmoid activation function.
Sigmoid activation function solved example,
Sigmoid activation function Numerical example,
Sigmoid activation function example
Sigmoid function solved example,
Sigmoid function numerical example,
Sigmoid function example
********************************
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4. Like, Share, Subscribe, and Don't forget to press the bell ICON for regular updates
3. Sigmoid Activation Function Solved Example | Soft Computing | Artificial Neural Network | Machine Learning | Data Mining Mahesh Huddar
The following concepts are discussed:
______________________________
How to find the output of the neuron Y using
the binary sigmoid activation function and
the bipolar sigmoid activation function.
Sigmoid activation function solved example,
Sigmoid activation function Numerical example,
Sigmoid activation function example
Sigmoid function solved example,
Sigmoid function numerical example,
Sigmoid function example
********************************
1. Blog / Website: https://www.vtupulse.com/
2. Like Facebook Page: https://www.facebook.com/VTUPulse
3. Follow us on Instagram: https://www.instagram.com/vtupulse/
4. Like, Share, Subscribe, and Don't forget to press the bell ICON for regular updates
What is the sigmoid activation function used in artificial neural networks?
👉 To gain early access to the full Deep Learning Dictionary course, register at:
🔗 ...
What is the sigmoid activation function used in artificial neural networks?
👉 To gain early access to the full Deep Learning Dictionary course, register at:
🔗 https://deeplizard.com/course/ddcpailzrd
👉 For more in depth lessons, check out the Deep Learning Fundamentals course:
🔗 https://deeplizard.com/course/dlcpailzrd
🕒🦎 VIDEO SECTIONS 🦎🕒
00:00 Welcome to DEEPLIZARD - Go to deeplizard.com for learning resources
00:10 Sigmoid Activation Function
02:21 Collective Intelligence and the DEEPLIZARD HIVEMIND
💥🦎 DEEPLIZARD COMMUNITY RESOURCES 🦎💥
👋 Hey, we're Chris and Mandy, the creators of deeplizard!
👉 Check out the website for more learning material:
🔗 https://deeplizard.com
💻 ENROLL TO GET DOWNLOAD ACCESS TO CODE FILES
🔗 https://deeplizard.com/resources
🧠 Support collective intelligence, join the deeplizard hivemind:
🔗 https://deeplizard.com/hivemind
🧠 Use code DEEPLIZARD at checkout to receive 15% off your first Neurohacker order
👉 Use your receipt from Neurohacker to get a discount on deeplizard courses
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👀 CHECK OUT OUR VLOG:
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❤️🦎 Special thanks to the following polymaths of the deeplizard hivemind:
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Ling Li
🚀 Boost collective intelligence by sharing this video on social media!
👀 Follow deeplizard:
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YouTube: https://youtube.com/deeplizard
🎓 Deep Learning with deeplizard:
Deep Learning Dictionary - https://deeplizard.com/course/ddcpailzrd
Deep Learning Fundamentals - https://deeplizard.com/course/dlcpailzrd
Learn TensorFlow - https://deeplizard.com/course/tfcpailzrd
Learn PyTorch - https://deeplizard.com/course/ptcpailzrd
Natural Language Processing - https://deeplizard.com/course/txtcpailzrd
Reinforcement Learning - https://deeplizard.com/course/rlcpailzrd
Generative Adversarial Networks - https://deeplizard.com/course/gacpailzrd
🎓 Other Courses:
DL Fundamentals Classic - https://deeplizard.com/learn/video/gZmobeGL0Yg
Deep Learning Deployment - https://deeplizard.com/learn/video/SI1hVGvbbZ4
Data Science - https://deeplizard.com/learn/video/d11chG7Z-xk
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❤️ Please use the knowledge gained from deeplizard content for good, not evil.
What is the sigmoid activation function used in artificial neural networks?
👉 To gain early access to the full Deep Learning Dictionary course, register at:
🔗 https://deeplizard.com/course/ddcpailzrd
👉 For more in depth lessons, check out the Deep Learning Fundamentals course:
🔗 https://deeplizard.com/course/dlcpailzrd
🕒🦎 VIDEO SECTIONS 🦎🕒
00:00 Welcome to DEEPLIZARD - Go to deeplizard.com for learning resources
00:10 Sigmoid Activation Function
02:21 Collective Intelligence and the DEEPLIZARD HIVEMIND
💥🦎 DEEPLIZARD COMMUNITY RESOURCES 🦎💥
👋 Hey, we're Chris and Mandy, the creators of deeplizard!
👉 Check out the website for more learning material:
🔗 https://deeplizard.com
💻 ENROLL TO GET DOWNLOAD ACCESS TO CODE FILES
🔗 https://deeplizard.com/resources
🧠 Support collective intelligence, join the deeplizard hivemind:
🔗 https://deeplizard.com/hivemind
🧠 Use code DEEPLIZARD at checkout to receive 15% off your first Neurohacker order
👉 Use your receipt from Neurohacker to get a discount on deeplizard courses
🔗 https://neurohacker.com/shop?rfsn=6488344.d171c6
👀 CHECK OUT OUR VLOG:
🔗 https://youtube.com/deeplizardvlog
❤️🦎 Special thanks to the following polymaths of the deeplizard hivemind:
Tammy
Mano Prime
Ling Li
🚀 Boost collective intelligence by sharing this video on social media!
👀 Follow deeplizard:
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Patreon: https://patreon.com/deeplizard
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🎓 Deep Learning with deeplizard:
Deep Learning Dictionary - https://deeplizard.com/course/ddcpailzrd
Deep Learning Fundamentals - https://deeplizard.com/course/dlcpailzrd
Learn TensorFlow - https://deeplizard.com/course/tfcpailzrd
Learn PyTorch - https://deeplizard.com/course/ptcpailzrd
Natural Language Processing - https://deeplizard.com/course/txtcpailzrd
Reinforcement Learning - https://deeplizard.com/course/rlcpailzrd
Generative Adversarial Networks - https://deeplizard.com/course/gacpailzrd
🎓 Other Courses:
DL Fundamentals Classic - https://deeplizard.com/learn/video/gZmobeGL0Yg
Deep Learning Deployment - https://deeplizard.com/learn/video/SI1hVGvbbZ4
Data Science - https://deeplizard.com/learn/video/d11chG7Z-xk
Trading - https://deeplizard.com/learn/video/ZpfCK_uHL9Y
🛒 Check out products deeplizard recommends on Amazon:
🔗 https://amazon.com/shop/deeplizard
🎵 deeplizard uses music by Kevin MacLeod
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❤️ Please use the knowledge gained from deeplizard content for good, not evil.
#IntuitiveDeepLearning #SimpleMathematicsOfDL #linearalgebra
The ANNOTATED summary of this lecture 3.5 is available at:
https://drive.google.com/file/d/1WgiBYf...
#IntuitiveDeepLearning #SimpleMathematicsOfDL #linearalgebra
The ANNOTATED summary of this lecture 3.5 is available at:
https://drive.google.com/file/d/1WgiBYf6pYsgZLCDZBao69FWYHXzwBssj/view?usp=sharing
In this DL map video we briefly cover the following topics:
1. How a simple linear 1-1-1 neural model operates with/out bias
2. How a simple non-linear 1-1-1 neural model operates with/out bias
3. Going deeper and adding more hidden units
4. Loss differentiation
5. Batching
📚🔗 The ANNOTATED summary map of the DL linear algebra of the second lecture videos 3.1 to 3.4 can be found at: https://drive.google.com/file/d/1pgr7uEepG3VTHalo4CyyO9yJtS07xp81/view?usp=sharing
📚🔗 The CLEAN summary map of the DL linear algebra of the second lecture videos 3.1 to 3.4 can be found at: https://drive.google.com/file/d/1NCP3x5g09yEH1OTASXHitgV6m6lJunMs/view?usp=sharing
Unlock the world of Deep Learning with our new “Intuitive Deep Learning” video series!
🚀 Dive into the mathematical foundations of DL using an intuitive approach and the power of linear algebra.
🧠 We hope that you will find the joy of clarity and multi-layer understanding of DL methods in this new series.
📊💡 Join us on this journey to gain a simplified understanding of complex concepts in DL.
Special thanks go to Jeremey Watts, Simon Prince and co-authors for producing foundational textbooks:
• Machine Learning Refined; https://github.com/jermwatt/machine_learning_refined
• Understanding Deep Learning; https://github.com/udlbook/
#IntuitiveDeepLearning #SimpleMathematicsOfDL #linearalgebra
The ANNOTATED summary of this lecture 3.5 is available at:
https://drive.google.com/file/d/1WgiBYf6pYsgZLCDZBao69FWYHXzwBssj/view?usp=sharing
In this DL map video we briefly cover the following topics:
1. How a simple linear 1-1-1 neural model operates with/out bias
2. How a simple non-linear 1-1-1 neural model operates with/out bias
3. Going deeper and adding more hidden units
4. Loss differentiation
5. Batching
📚🔗 The ANNOTATED summary map of the DL linear algebra of the second lecture videos 3.1 to 3.4 can be found at: https://drive.google.com/file/d/1pgr7uEepG3VTHalo4CyyO9yJtS07xp81/view?usp=sharing
📚🔗 The CLEAN summary map of the DL linear algebra of the second lecture videos 3.1 to 3.4 can be found at: https://drive.google.com/file/d/1NCP3x5g09yEH1OTASXHitgV6m6lJunMs/view?usp=sharing
Unlock the world of Deep Learning with our new “Intuitive Deep Learning” video series!
🚀 Dive into the mathematical foundations of DL using an intuitive approach and the power of linear algebra.
🧠 We hope that you will find the joy of clarity and multi-layer understanding of DL methods in this new series.
📊💡 Join us on this journey to gain a simplified understanding of complex concepts in DL.
Special thanks go to Jeremey Watts, Simon Prince and co-authors for producing foundational textbooks:
• Machine Learning Refined; https://github.com/jermwatt/machine_learning_refined
• Understanding Deep Learning; https://github.com/udlbook/
Watch on Udacity: https://www.udacity.com/course/viewer#!/c-ud262/l-315142919/m-432088680
Check out the full Advanced Operating Systems course for free at: http...
Watch on Udacity: https://www.udacity.com/course/viewer#!/c-ud262/l-315142919/m-432088680
Check out the full Advanced Operating Systems course for free at: https://www.udacity.com/course/ud262
Georgia Tech online Master's program: https://www.udacity.com/georgia-tech
Watch on Udacity: https://www.udacity.com/course/viewer#!/c-ud262/l-315142919/m-432088680
Check out the full Advanced Operating Systems course for free at: https://www.udacity.com/course/ud262
Georgia Tech online Master's program: https://www.udacity.com/georgia-tech
In this video we discuss the sigmoid function.
The sigmoid function plays an important role in the field of machine learning and is considered as one of the most widely used so-called activation functions.
More specifically, in the context of logistic regression, the sigmoid is used to predict the outcome of binary classification problems.
#sigmoid #machinelearning #logisitcregression #binaryclassification
Sigmoid is used as an activation function in lot of machine learning problem,In this video I have tried to explain sigmoid function with very simple example.
A sigmoid function can convert any real value sample to a probability range of 0 to 1 this property of sigmoid help's to utilize it logistic regression problems.
In the further session we have explained logic regression here is the link for the video..
https://www.youtube.com/watch?v=6Q2SXLuv-4E
For a complete index of all the machine learning videos, check out:
https://www.youtube.com/channel/UCoB1kaaQrQEkB-ud2QxmgUQ/videos
Why do we use the mathematical constant "e" in the sigmoid function?
My Patreon : https://www.patreon.com/user?u=49277905
Sigmoid Video : https://www.youtube.com/watch?v=Aj7O9qRNJPY
Visuals Created with Excalidraw : https://excalidraw.com/
This video explains why we use the sigmoid function in neural networks for machine learning, especially for binary classification. We consider both the practical side of making sure we get a consistent gradient from the standard categorical loss function, as well as making sure the equation is easily computable. We also look at the statistical side by giving an interpretation for what the logit values represent (the values passed into the sigmoid function), and how they can be thought of as normally distributed values with their means shifted one way or the other depending on which class they are for.
My other video, "Derivative of Sigmoid and Softmax Explained Visually":
📼 https://youtu.be/gRr2Q97XS2g
The Desmos graph of the sigmoid function:
📈https://www.desmos.com/calculator/hjc4peyxmc
Connect with me:
🐦 Twitter - https://twitter.com/elliotwaite
📷 Instagram - https://www.instagram.com/elliotwaite
👱 Facebook - https://www.facebook.com/elliotwaite
💼 LinkedIn - https://www.linkedin.com/in/elliotwaite
Join our Discord community:
💬 https://discord.gg/cdQhRgw
🎵 Kazukii - Return
→ https://soundcloud.com/ohthatkazuki
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Wondering what all those sigmoid functions are for and why you see them all over machine learning? The answer is simple and it has to do with something you'd learn on day 1 of an economics 101 class...
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3. Sigmoid Activation Function Solved Example | Soft Computing | Artificial Neural Network | Machine Learning | Data Mining Mahesh Huddar
The following concepts are discussed:
______________________________
How to find the output of the neuron Y using
the binary sigmoid activation function and
the bipolar sigmoid activation function.
Sigmoid activation function solved example,
Sigmoid activation function Numerical example,
Sigmoid activation function example
Sigmoid function solved example,
Sigmoid function numerical example,
Sigmoid function example
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What is the sigmoid activation function used in artificial neural networks?
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A sigmoid function is a mathematical function having an "S" shape (sigmoid curve). Often, sigmoid function refers to the special case of the logistic function shown in the first figure and defined by the formula
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. The differential equation 
, with the inclusion of a 
, provides a class of functions of this type.
