Lesson Index

[tyoc213]

Deep Learning

Welcome to Part 1 (v2)

Use this category for discussions of Practical Deep Learning for Coders (2018), Part 1. Be sure to check the FAQ before posting, and read about how to ask for help. Here are threads to help you with specific issues: Paperspace setup Finally, here’s the introduction thread where you can get to know the other students and introduce yourself.

Lesson		Video	Discussion
1	Recognizing cats and dogs	https://youtu.be/IPBSB1HLNLo	Wiki: Lesson 1
2	Convolutional Neural Networks	https://youtu.be/JNxcznsrRb8	Wiki: Lesson 2
3	Improving Your Image Classifier	https://youtu.be/9C06ZPF8Uuc	Wiki: Lesson 3
4	Structure, Time Series, & Lenguage Models	https://youtu.be/gbceqO8PpBg	Wiki: Lesson 4
5	Collaborative Filtering; Inside The Training Loop	https://youtu.be/J99NV9Cr75I	Wiki: Lesson 5
6	Interpreting Embeddings; RNNs From Scratch	https://youtu.be/sHcLkfRrgoQ	Wiki: Lesson 6
7	ResNet From Scratch	https://youtu.be/H3g26EVADgY	Wiki: Lesson 7

About the Part 2 & Alumni (2018) category

Use this category for discussions of Cutting Edge Deep Learning for Coders (2018), Part 2. Also use this category if you’ve finished the course and want to discuss topics that may be of interest to other part 2 students and alumni. For topics that aren’t mentioned in the course, like RL, tensorflow, etc, and for general interest topics such as AI news, please use the #deep-learning forum. Here’s is a link to all the lesson resources for this part: Lesson Discussion Lesson 8 Part 2 Les…

Lesson		Video	Discussion
8		https://youtu.be/b8D6Bwck9QM	Part 2 Lesson 8 wiki
9		https://youtu.be/2HKbG7bGRIM	Part 2 Lesson 9 wiki
10		https://youtu.be/_ercfViGrgY	Part 2 Lesson 10 wiki
11		https://youtu.be/NFVKDa5W35I	Part 2 lesson 11 wiki
12		https://youtu.be/UqpwXKtkgvk	Part 2 Lesson 12 wiki
13		https://youtu.be/HbngrIU7uPA	Part 2 Lesson 13 Wiki - #67 by LCasu

Linear Algebra

About the Computational Linear Algebra category

This category is for questions and discussions related to the fast.ai course, Computational Linear Algebra. This blog post introduces the course. Here is advice on how to ask for help in a way that maximizes the chances someone else will be able to provide a helpful answer. The primary resource for this course is the free online textbook of Jupyter Notebooks, available on Github. Accompanying the notebooks is a playlist of lecture videos, available on YouTube. If you are ever confused by a le…

#	Lesson	Video
1	Matrix Math, Accuracy, Memory, Speed, & Parallelization	https://youtu.be/8iGzBMboA0I&list=PLtmWHNX-gukIc92m1K0P6bIOnZb-mg0hY
2	Topic Modelling with SVD & NMF	https://youtu.be/kgd40iDT8yY&list=PLtmWHNX-gukIc92m1K0P6bIOnZb-mg0hY
3	Review, New Perspective on NMF, & Randomized SVD	https://youtu.be/C8KEtrWjjyo
4	Randomized SVD & Robust PCA	https://youtu.be/Ys8R2nUTOAk
5	Robust PCA & LU Factorization	https://youtu.be/O2x5KPJr5ag
6	Block Matrix Mult, Broadcasting, & Sparse Storage	https://youtu.be/YY9_EYNj5TY
7	Compressed Sensing for CT Scans	https://youtu.be/ZUGkvIM6ehM
8	Numba, Polynomial Features, How to Implement Linear Regression	https://youtu.be/SjX55V8zDXI
9	PageRank with Eigen Decompositions	https://youtu.be/AbB-w77yxD0
10	QR Algorithm to find Eigenvalues, Implementing QR Decomposition	https://youtu.be/1kw8bpA9QmQ

Machine Learning

Another treat! Early access to Intro To Machine Learning videos

We’ll be officially releasing a new course (tentatively) called Machine Learning For Coders soon (it’s not up on the website yet). It’s being recorded with the masters students at MSAN. I’ve decided to share the videos with you all as well, since for those of you that haven’t done any ML before, you might find this a helpful additional resource. It uses the same fastai library as our deep learning course, so your existing repo and AWS instance will work fine. Here’s the videos - I’ll update thi…

Lesson #	Video
1	https://youtu.be/CzdWqFTmn0Y
2	https://youtu.be/blyXCk4sgEg
3	https://youtu.be/YSFG_W8JxBo
4	https://youtu.be/0v93qHDqq_g
5	https://youtu.be/3jl2h9hSRvc
6	https://youtu.be/BFIYUvBRTpE
7	https://youtu.be/O5F9vR2CNYI
8	https://youtu.be/DzE0eSdy5Hk
9	https://youtu.be/PGC0UxakTvM
10	https://youtu.be/37sFIak42Sc
11	https://youtu.be/XJ_waZlJU8g
12	https://youtu.be/5_xFdhfUnvQ

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And finally we have

http://forums.fast.ai/t/about-the-theory-category/2620
And sure theory section and some external videos http://forums.fast.ai/t/deep-learning-book-video-summaries/6503

So yeah, there are lot of free resources thanks!.

[jeremy (Jeremy Howard)]

Thanks this is very helpful!

[Abbas]

tyoc213. Thank you very much.

[tyoc213]

Hope someone find it useful to have all in once place, I also added the algebra and Machine Learning along with a ref to the theory section.

[annahaz]

Thank you!! Really helpful!

[tyoc213]

Cant edit original post anymore, but here is the addition of

FAQ, resources, and official course updates

Welcome to deep learning part 1 v3! This thread will be updated with any important changes to the course, so please keep a close eye on it. Only admins are able to reply to this thread, so please subscribe to topic notifications to ensure you don’t miss anything. Click “none” in the sub-forum list at the top of the category to hide all the local discussions, if you want to reduce the amount of topics you see. Use the “Advanced” sub-forum for any discussions not accessible to deep learning beginn…

#	Original	youtube	Title
1	https://course.fast.ai/videos/?lesson=1	https://youtu.be/XfoYk_Z5AkI	Image classification
2	https://course.fast.ai/videos/?lesson=2	https://youtu.be/ccMHJeQU4Qw	Data cleaning and production; SGD from scratch
3	https://course.fast.ai/videos/?lesson=3	https://youtu.be/MpZxV6DVsmM	Data blocks; Multi-label classification; Segmentation
4	https://course.fast.ai/videos/?lesson=4	https://youtu.be/qqt3aMPB81c	NLP; Tabular data; Collaborative filtering; Embeddings
5	https://course.fast.ai/videos/?lesson=5	https://youtu.be/CJKnDu2dxOE	Back propagation; Accelerated SGD; Neural net from scratch
6	https://course.fast.ai/videos/?lesson=6	https://youtu.be/hkBa9pU-H48	Regularization; Convolutions; Data ethics
7	https://course.fast.ai/videos/?lesson=7	https://youtu.be/9spwoDYwW_I	Resnets from scratch; U-net; Generative (adversarial) networks