MIT Computational Biology: Genomes, Networks, Evolution, Health
http://compbio.mit.edu/6.047/
Prof. Manolis Kellis

Full playlist with all videos in order is here: https://www.youtube.com/playli....st?list=PLypiXJdtIca

All slides from Fall 2019 are here: https://stellar.mit.edu/S/cour....se/6/fa19/6.047/mate

Outline for this lecture:
1. Supervised Learning with Neural networks
- Perceptron, layers, activation units (sigmoid, softplus, ReLU)
- Learning: Gradient, Back-propagation, Rate, Dropout, Overfitting
2. Unsupervised learning with Deep belief networks & autoencoders
- Boltzmann machines, Restricted BMs (RBMs), Deep belief networks
- Learning: Energy, Gibbs Sampling, Simulated Annealing, Wake-sleep
3. Modern deep learning architectures
- Auto-encoders: Self-training, representation learning, RBM pre-training
- Convolutional neural networks: convolutional filters, pooling (sum/max)
- Recurrent neural networks: learning linear/temporal relationships
- Transfer learning, generative adversarial networks (GANs)
4. Deep learning in regulatory genomics
- Deciphering tissue-specific splicing code
- Deciphering regulatory grammars. DeepBind, DeepSea, Basset.
5. Three-dimensional structures: protein-DNA interactions, drug design
- Modern deep learning computing infrastructure
- Engines: TensorFlow, Theano, Torch, Caffe. Envs: Keras, Lasagene

#chatgpt #artificialintelligence #openai
Super simple guide on How to Fine Tune ChatGPT, in a Beginners Guide to Building Businesses w/ GPT-3. Knowing how to Fine Tune GPT-3 is one of the most important skills you can have as an entrepreneur to build your own ChatGPT site or get into the AI industry and build a valuable business business.

While limited in scope, this video gives you a clear breakdown of the stages in fine tuning these models.

Kaggle Dataset:
https://www.kaggle.com/dataset....s/thedevastator/unlo

Prompts & Code HERE:
https://docs.google.com/docume....nt/d/1jJbk61grxYZV2q

My AI Consulting Services 👋🏼
Want to speak with me about your next big project? Book here:
https://calendly.com/liamottley/consulting-call

Join My Newsletter! 🗞️
Get your fix of the latest AI news direct to your inbox:
https://morningsideai.beehiiv.com/

My AI Entrepreneurship Community 📈
Find top shelf co-founders for your next AI venture:
http://discord.gg/dAa78Zj7yj

My Links 🔗
👉🏻 Subscribe: https://www.youtube.com/channe....l/UCui4jxDaMb53Gdh-A
👉🏻 Twitter: https://twitter.com/liamottley_
👉🏻 LinkedIn: https://www.linkedin.com/in/liamottley/
👉🏻 Instagram: https://instagram.com/liamottley

Timestamps:
0:00 - Intro
1:07 - Generating Pairs
7:11 - Fine Tuning w/ API
10:18 - Running Our App
12:38 - Outro

About Me 👋🏼
Hi! My name is Liam Ottley and I’m an AI developer and entrepreneur, founder of my own AI development company: Morningside AI (https://morningside.ai). You’ve found my YouTube channel where I help other entrepreneur’s wrap their heads around AI with tutorials on how to get started with building AI apps!

With developments in AI moving so fast, I’m constantly working on my own projects and those of clients and sharing my learnings with my viewers 2-3x per week.

I don’t have anything to sell you, my only hope is that one day some of you will learn enough from my videos to see an exciting opportunity in the AI space and want to work with my development company to make it a reality.

Did you ever wonder how to create a BERT or GPT2 tokenizer in your own language or on your own corpus? This video will teach you how to do this with any tokenizer of the 🤗 Transformers library.

This video is part of the Hugging Face course: http://huggingface.co/course
Open in colab to run the code samples:
https://colab.research.google.....com/github/huggingfa

Related videos:
- Building a new tokenizer: https://youtu.be/MR8tZm5ViWU

Don't have a Hugging Face account? Join now: http://huggingface.co/join
Have a question? Checkout the forums: https://discuss.huggingface.co/c/course/20
Subscribe to our newsletter: https://huggingface.curated.co/

** Data Science Certification using R: https://www.edureka.co/data-science **
This Edureka "Data Science Applications" video takes you through the various domains in which data science is being deployed today, along with some potential applications of this technology. The world today runs on data and this video shows exactly that.

Check out our Data Science Tutorial blog series: http://bit.ly/data-science-blogs

Check out our complete Youtube playlist here: http://bit.ly/data-science-playlist

-------------------------------------

Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV

Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka

#datascience #statisticsfordatascience #rstatistics #datascienceessentials #datasciencewithr
--------------------------------------
How it Works?


1. This is a 30-hour Instructor-led Online Course.

2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.

3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!


-------------------------------------

About the Course
Edureka's Data Science Training lets you gain expertise in Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes using R. Data Science Training encompasses a conceptual understanding of Statistics, Time Series, Text Mining and an introduction to Deep Learning. Throughout this Data Science Course, you will implement real-life use-cases on Media, Healthcare, Social Media, Aviation and HR.

-------------------------------------

Who should go for this course?

The market for Data Analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals. Our Data Science Training helps you to grab this opportunity and accelerate your career by applying the techniques on different types of Data. It is best suited for:
Developers aspiring to be a 'Data Scientist'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
'R' professionals who wish to work Big Data
Analysts wanting to understand Data Science methodologies

-------------------------------------

Why learn Data Science?
Data science is an evolutionary step in interdisciplinary fields like the business analysis that incorporate computer science, modelling, statistics and analytics. To take complete benefit of these opportunities, you need a structured training with an updated curriculum as per current industry requirements and best practices.
Besides strong theoretical understanding, you need to work on various real-life projects using different tools from multiple disciplines to gather a data set, process and derive insights from the data set, extract meaningful data from the set, and interpret it for decision-making purposes.
Additionally, you need the advice of an expert who is currently working in the industry tackling real-life data-related challenges.

-------------------------------------

Got a question on the topic?
Please share it in the comment section below and our experts will answer it for you.

For Data Science Training and Certification, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).

People don’t understand the scale of the Universe. There’s a data driven way to read the news: go to https://ground.news/veritasium to get 30% off the Vantage plan and see through sensationalized reporting.

If you’re looking for a molecular modeling kit, try Snatoms – a kit I invented where the atoms snap together magnetically – https://ve42.co/SnatomsV


▀▀▀
A huge thank you to Dr. Ashmeet Singh for his expert feedback on this video.


▀▀▀
References:
Fun video by RealLifeLore about the scale of the Universe - https://www.youtube.com/watch?v=Iy7NzjCmUf0&pp=ygUkcmVhbCBsaWZlIGxvcmUgc2NhbGUgb2YgdGhlIHVuaXZlcnNl
Moon Facts via NASA - https://ve42.co/NASAMoon
Titan Facts via NASA - https://ve42.co/Titan
Mercury Facts via NASA - https://ve42.co/Mercury
Why Pluto is no Longer a Planet, BBC News via YouTube - https://www.youtube.com/watch?v=iIk29MnzZWA&pp=ygUYcGx1dG8gbm8gbG9uZ2VyIGEgcGxhbmV0
Pluto, Wikipedia - https://ve42.co/WikiPluto
Eris, Wikipedia - https://ve42.co/WikiEris
Brown, M. E., & Schaller, E. L. (2007). The mass of dwarf planet Eris. Science, 316(5831), 1585-1585. - https://ve42.co/Brown2007
Trans-Neptunian object, Wikipedia - https://ve42.co/WikiTNO
IAU 2006 General Assembly Press Release, via IAU - https://ve42.co/IAU2006
Solar System Moons via NASA - https://ve42.co/NASAMoons
Solar System Asteroids via NASA - https://ve42.co/Asteroids
Solar System, Wikipedia - https://ve42.co/WikiSolarSystem
How many stars are in the Universe via ESA - https://ve42.co/ESAStars
Catalog of Exoplanets via exoplanet - https://ve42.co/ExoplanetCatalog
Crowther, T. W., Glick, H. B., Covey, K. R., Bettigole, C., Maynard, D. S., Thomas, S. M., ... & Bradford, M. A. (2015). Mapping tree density at a global scale. Nature, 525(7568), 201-205. - https://ve42.co/Crowther2015
Galaxy, Wikipedia - https://ve42.co/WikiGalaxy
Counting Galaxies with the Hubble Space Telescope via NASA - https://ve42.co/CountingGalaxies
Conselice, C. J., Wilkinson, A., Duncan, K., & Mortlock, A. (2016). The evolution of galaxy number density at z8 and its implications. The Astrophysical Journal, 830(2), 83. - https://ve42.co/Conselice2016
Sagan, C., & Druyan, A. (2011). Pale blue dot: A vision of the human future in space. Ballantine books.

Images & Video:
Clip of Titan’s Surface, NASA via YouTube - https://www.youtube.com/watch?v=xn3-0a19sC8
Clips of Pluto Had it Coming, The Late Show with Stephen Colbert via YouTube - https://www.youtube.com/watch?v=5nqT7XrYRPc
Image of Solar System Objects - https://ve42.co/SolarSystemObjects


▀▀▀
Special thanks to our Patreon supporters:
Adam Foreman, Anton Ragin, Balkrishna Heroor, Bill Linder, Blake Byers, Burt Humburg, Chris Harper, Dave Kircher, David Johnston, Diffbot, Evgeny Skvortsov, Gnare, John H. Austin, Jr., john kiehl, Josh Hibschman, Juan Benet, KeyWestr, Lee Redden, Marinus Kuivenhoven, Max Paladino, Meekay, meg noah, Michael Krugman, Paul Peijzel, Richard Sundvall, Sam Lutfi, Stephen Wilcox, Tj Steyn, TTST, Ubiquity Ventures


▀▀▀
Directed by Casper Mebius
Written by Casper Mebius and Derek Muller
Additional research & fact checking by Gregor Čavlović
Edited by Peter Nelson
Animated by Ivy Tello and Alondra Vitae
Filmed by Derek Muller, Raquel Nuno and Zyan Treadwell
Produced by Derek Muller, Casper Mebius and Han Evans

Additional video/photos supplied by Getty Images, StoryBlocks and by courtesy of NASA, NASA's Goddard Space Flight Center/SDO, NASA JPL, NASA/JPL-Caltech NASA GSFC, NASA HQ, NASA's Scientific Visualization Studio, NCSA, A. Kritsuk, M. Norman

Music from Epidemic Sound
Thumbnail by Peter Sheppard