Previous Video:- https://www.youtube.com/watch?v=U7BSo_1IVs4 Next Video:- https://www.youtube.com/watch?v=e4dsTsAGV-Q ✔️📚👉 Watch Full Free Course:- https://www.magnetbrains.com ✔️📚👉 Get Notes Here: https://www.pabbly.com/out/magnet-brains ✔️📚👉 Get All Subjects playlists:- ​https://www.pabbly.com/out/all-videos-playlist ✔️📚👉 Student Feedback Form: https://forms.pabbly.com/form/share/eQaF-477327 ======================================================= ✅ In this video, ✔️ Class: 10th ✔️ Subject: Artificial Intelligence ✔️ Chapter: Introduction To AI – Foundational Concepts (Chapter 1) ✔️ Topic Name: Intelligence and Traits of Intelligence ✔️ Topics Covered in This Video: Definition of Intelligence, Traits of Intelligence:- Musical intelligence, Mathematical logic intelligence, Spatial visual intelligence, Linguistic intelligence, Kinesthetic intelligence, Linguistic intelligence, Naturalist intelligence and more ======================================================= 📢 🔥 Available (Kindergarten to 12th) all Video Subject wise Playlist https://www.pabbly.com/out/all-videos-playlist Why study from Magnet Brains? Magnet Brains is an online education platform that helps gives You NCERT/CBSE curriculum based free full courses from Kindergarten to Class 12th so that you can perform well in any and all exams you give in your academic career. 👉 Contact us 🤑🤑 ➡️ Connect with us : magnetbrainsbhopal@gmail.com ➡️ Website : https://www.magnetbrains.com/ ➡️ Subscribe to us on YouTube: http://www.youtube.com/channel/UC3HS6… ➡️ Subscribe to Magnet Brains Hindi Medium : https://www.youtube.com/channel/UCwO6… ➡️ Facebook : https://www.facebook.com/Magnet-Brain ➡️ Instagram : https://www.instagram.com/magnetbrains/ ➡️ Telegram : https://t.me/magnetbrainsbhopal
Help fund future projects: https://www.patreon.com/3blue1brown An equally valuable form of support is to simply share some of the videos. Special thanks to these supporters: http://3b1b.co/nn3-thanks This one is a bit more symbol-heavy, and that’s actually the point. The goal here is to represent in somewhat more formal terms the intuition for how backpropagation works in part 3 of the series, hopefully providing some connection between that video and other texts/code that you come across later. For more on backpropagation: http://neuralnetworksanddeeplearning.com/chap2.html https://github.com/mnielsen/neural-networks-and-deep-learning http://colah.github.io/posts/2015-08-Backprop/ Music by Vincent Rubinetti: https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown —————— Video timeline 0:00 – Introduction 0:38 – The Chain Rule in networks 3:56 – Computing relevant derivatives 4:45 – What do the derivatives mean? 5:39 – Sensitivity to weights/biases 6:42 – Layers with additional neurons 9:13 – Recap —————— 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): http://3b1b.co/subscribe 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
What’s actually happening to a neural network as it learns? Next chapter: https://youtu.be/tIeHLnjs5U8 Help fund future projects: https://www.patreon.com/3blue1brown An equally valuable form of support is to simply share some of the videos. Special thanks to these supporters: http://3b1b.co/nn3-thanks And by CrowdFlower: http://3b1b.co/crowdflower Home page: https://www.3blue1brown.com/ The following video is sort of an appendix to this one. The main goal with the follow-on video is to show the connection between the visual walkthrough here, and the representation of these “nudges” in terms of partial derivatives that you will find when reading about backpropagation in other resources, like Michael Nielsen’s book or Chis Olah’s blog. Video timeline: 0:00 – Introduction 0:23 – Recap 3:07 – Intuitive walkthrough example 9:33 – Stochastic gradient descent 12:28 – Final words
Artificial General Intelligence – AGI might be the last invention of mankind. For better or for worse. Artificial intelligence is very beneficial to society in today’s age. AI will probably continue to be beneficial in the coming decades. However, as intelligent machines continue to improve, with the development of a true AGI or artificial general intelligence, there might be a serious threat to humanity. This issue is known as the AI control problem or the AI alignment problem. The risks involved in the process of improving intelligent systems might be intrinsic to intelligent machines that are goal-oriented. Today’s AI are known as narrow AI. They are able to beat humans in specifics tasks like chess but the same AI can not beat humans across multiple domains. At least not yet. A true artificial general intelligence might be able to solve some of the deepest secrets of nature. It might run simulations and come up with new mathematical equations and models to solve seemingly unsolvable problems in science. Such an intelligent machine might be able to cure any disease and create a wealth of sorts we’ve only seen in science fiction. It is difficult for many people to take the AI control problem seriously. Not just for the general public but also for researchers and some computer scientists who are themselves involved in the creation of tomorrow’s AI. The skeptics for this thesis do not bring forth any compelling argument why we shouldn’t be concerned about AI. To say AGI is [More]
Click here to Subscribe to SET India: https://www.youtube.com/channel/UCpEhnqL0y41EpW2TvWAHD7Q?sub_confirmation=1 Paul and Muskan perform a robotic dance on “Apsara Ali” that impresses their judges!
Click here to Subscribe to SET India: https://www.youtube.com/channel/UCpEhnqL0y41EpW2TvWAHD7Q?sub_confirmation=1 Deepika gives her all out in doing a robotic dance on “Nagada Sang Dhol”!
After browsing and trying out over 4 different courses from multiple learning platforms this course from PY4E really stood out. Without any programming knowledge, I used this course to build my own payroll and incentive calculation system for my organization that employs over 100 people. Course Curator Certified Best Python Cousre on the Web. Dr. Charles Severance is truely a gifted educator who can simplify complex topics in to easy to USE, bite sized episodes that help you learn whats needed to start building applications right away! Please visit https://www.py4e.com/ to get additional information on the course. You can take this course for a certificate as the Python for Everybody Specialization on Coursera at https://www.coursera.org/specializations/python
Home page: https://www.3blue1brown.com/ Brought to you by you: http://3b1b.co/nn2-thanks And by Amplify Partners. For any early stage ML startup founders, Amplify Partners would love to hear from you via 3blue1brown@amplifypartners.com To learn more, I highly recommend the book by Michael Nielsen http://neuralnetworksanddeeplearning.com/ The book walks through the code behind the example in these videos, which you can find here: https://github.com/mnielsen/neural-networks-and-deep-learning MNIST database: http://yann.lecun.com/exdb/mnist/ Also check out Chris Olah’s blog: http://colah.github.io/ His post on Neural networks and topology is particular beautiful, but honestly all of the stuff there is great. And if you like that, you’ll *love* the publications at distill: https://distill.pub/ For more videos, Welch Labs also has some great series on machine learning: https://youtu.be/i8D90DkCLhI https://youtu.be/bxe2T-V8XRs “But I’ve already voraciously consumed Nielsen’s, Olah’s and Welch’s works”, I hear you say. Well well, look at you then. That being the case, I might recommend that you continue on with the book “Deep Learning” by Goodfellow, Bengio, and Courville. Thanks to Lisha Li (@lishali88) for her contributions at the end, and for letting me pick her brain so much about the material. Here are the articles she referenced at the end: https://arxiv.org/abs/1611.03530 https://arxiv.org/abs/1706.05394 https://arxiv.org/abs/1412.0233 Music by Vincent Rubinetti: https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown —————— 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 [More]