Manolis Kellis
6.874/6.802/20.390/20.490/HST.506 Spring 2021 Prof. Manolis Kellis
Deep Learning in the Life Sciences / Computational Systems Biology
Playlist: https://youtube.com/playlist?list=PLypiXJdtIca5sxV7aE3-PS9fYX3vUdIOX
Latest slides and course today: http://compbio.mit.edu/6874
Spring 2021 slides and materials: http://mit6874.github.io/
0:00 Course intro, staff, meeting times, prereqs, grade breakdown, links
07:19 Why Deep Learning in the Life Sciences
23:49 Extracting signal from noise
25:24 Modules: ML, Regulation, Variation, Folding, Imaging, Frontiers
30:36 Lectures, Scribing, Quiz, Guest Lectures
34:10 Projects, mentoring, teams, milestones, papers, resources
51:28 First day survey, year, major, timezone, background, drivers, guidance
54:28 Intelligence, Classical AI, Artificial Intelligence, Machine Learning, Representations
1:00:30 Bayesian Inference, Observed vs. Hidden, Parameter Estimation
1:03:30 Bayes’ Rule, Posterior, Likelihood, Prior, Marginal
1:05:40 Clustering, Classification, Feature Engineering, Feature Learning
1:08:27 Generative (model) vs. discriminative (separators) learning
1:11:09 Classification performance across range of thresholds
1:11:40 Network inference, linear algebra, dimensionality reduction, regularization
1:12:50 AI vs. Machine Learning vs. Representation Learning vs. Deep Learning
1:14:16 Deep representation learning through layers of abstraction
1:14:58 Human vision: layers, abstractions, representations, neuronal firing
1:16:20 Deep multi-layer architectures in mammalian, primate, and human brain
1:17:40 Neural network primitives, neurons, networks, non-linearities, gradient learning
1:18:23 Preview of backpropagation, overfitting, dropout, convolution, autoencoders
1:19:10 Conclusion, Questions, Compute Power of human, Interpretability, Goodbyes
Source
promising to be another great lecture series!
Manolis is an amazing teacher💚
Wow looking forward to the next episode!
You are such a great teacher, Prof. Manolis!! Thank you so much for sharing all your Knowledge with everyone! Looking forward to the Next class! 💯
This is amazing!
Who is excited for this course? I am excited for this course!
Super excited, thanks for sharing your excellent teachings
Thanks a lot for this playlist, hoping to get the rest of the videos soon!😊
Watching how organised these lectures are, and the quality of the teachers, I realise the quality of education in schools like MIT is huge when compared to other universities in other countries
Fantistic course! Thanks Manolis!!
Good job! Thank u for sharing!
Thanks for this playlist. Doing great work to democratize knowledge huge respect to you Prof Kellis and to MIT for providing these resources for free
I have watched your 4 talks on lex fridman podcast and just love the way you are able to articulate such ideas smoothly. So, that brought me here. Hope I am able to complete the course virtually.
Yes. Yes… Yes!!!
Thank you for sharing this. It's awesome!
The lecture is informative and engaging, but the noise in the background is very distracting.
Brilliant! Paint me introduced.
8:15 In future you will have a 4th convergence of Quantum computing.
I was an international college student in Boston, biology major, graduated in 2015, now been studying bioinformatics phD in South Korea. I came across with this video and loved it. Great lectures and very helpful. It reminds me of good times in US and made me want to go back for post-doc if possible. I just want to say thank you professor Kellies for sharing your excellent knowledge and thank you all in class. I really appreciate it.
Thank you for this great course.
Thank you for this great course.
thanks, i'm from computer science, this is very great
My neurons was stimulated by the signals from this lecture after sigmoid activation with last output layer the probability of excitement is 95% that was measured by binary accuracy.
Dear professoe, How can I access the problem sets? it is not on the course webpage.
HI Manolis, im a computational biology PhD student who likes this course! May I ask where to download these course materials?
Thanks for this Playlist. It's a great way to enter the field 🙂