Deep Learning SIMPLIFIED: The Series Intro - Ep. 1

Are you overwhelmed by overly-technical explanations of Deep Learning? If so, this series will bring you up to speed on this fast-growing field – without any of the math or code. Deep Learning is an important subfield of Artificial Intelligence (AI) that connects various topics like Machine Learning, Neural Networks, and Classification. The field has advanced significantly over the years due to the works of giants like Andrew Ng, Geoff Hinton, Yann LeCun, Adam Gibson, and Andrej Karpathy. Many companies have also invested heavily in Deep Learning and AI research - Google with DeepMind and its Driverless car, nVidia with CUDA and GPU computing, and recently Toyota with its new plan to allocate one billion dollars to AI research. Deep Learning TV on Facebook: https://www.facebook.com/DeepLearningTV/ Twitter: https://twitter.com/deeplearningtv You've probably looked up videos on YouTube and found that most of them contain too much math for a beginner. The few videos that promise to just present concepts are usually still too high level for someone getting started. Any videos that show complicated code just make these problems worse for the viewers. There’s nothing wrong with technical explanations, and to go far in this field you must understand them at some point. However, Deep Learning is a complex topic with a lot of information, so it can be difficult to know where to begin and what path to follow. Does this resonate with you? What are your thoughts? Please comment. The goal of this series is to give you a road map with enough detail that you’ll understand the important concepts, but not so much detail that you’ll feel overwhelmed. The hope is to further explain the concepts that you already know and bring to light the concepts that you need to know. In the end, you’ll be able to decide whether or not to invest additional time on this topic. So while the math and the code are important, you will see neither in this series. The focus is on the intuition behind Deep Learning – what it is, how to use it, who’s behind it, and why it’s important. You'll first get an overview of Deep Learning and a brief introduction of how to choose between different models. Then we'll see some use cases. After that, we’ll discuss various Deep Learning tools including important software libraries and platforms where you can build your own Deep Nets. Some resources: Andrew Ng's Machine learning class - https://www.coursera.org/learn/machine-learning Michael Nielsen's book: http://neuralnetworksanddeeplearning.com/index.html Credits: Nickey Pickorita (YouTube art) - https://www.upwork.com/freelancers/~0147b8991909b20fca Isabel Descutner (Voice) - https://www.youtube.com/user/IsabelDescutner Dan Partynski (Copy Editing) - https://www.linkedin.com/in/danielpartynski Marek Scibior (Prezi creator, Illustrator) - http://brawuroweprezentacje.pl/ Jagannath Rajagopal (Creator, Producer and Director) - https://ca.linkedin.com/in/jagannathrajagopal

Comments

1. Hmm. It says "Intro". Should I be upset that's its an Intro?
2. thanks a lot!! Your video help me to understand this topic!!
3. I LOVE YOU, THANK YOU FOR DOING THIS SERIES....
4. I watch the first 10 series of your video and this is completely scripted. I don't believe you understand this topic well enough to be presenting Deep Learning. There are other video much better than your series. Perhaps you can learn from others on how to present Deep Learning.
5. Looks like a good start. I was actually looking for a super simple, basic explanation of how it works. But if you can explain all of that simply and clearly, then why not!
6. Your content is very lovely, nice, beautiful, cute, brilliant and everything cool :)
7. 看了一下，感觉还不错的课程，订阅了。
8. But I want to be scared :(
9. Stupid video that didn't explain a thing
10. what about IBM Watson
11. i want to ask you if u have any idea about deep learning based recomondation system ?
12. awesome work, thank you!
13. Never heard of this. like to know more
14. Great work! 100 X better than all the useless TV programs people are addicted to.
    Keep up the good work.
15. Hi,
    How can I apply deep learning on detecting malware?
16. yes, "skip to the point"
17. Hi.. I am a non techie but this video helped a lot in understanding this subject. I would appreciate if you could guide / share how to go about making something using DL..
18. Great start!
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20. good