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Alfredo Canziani
@alfcnz
Musician, math lover, cook, dancer, 🏳️‍🌈, and an ass prof of Computer Science at New York University
New York University
Joined September 2012
Posts
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    Releasing the Energy-Book 🔋 from its first appendix's chapter, where I explain how I create my figures. 🎨 Feel free to report errors via the issues' tracker, contribute to the exercises, and show me what you can draw, via the discussion section. 🥳 github.com/Atcold/Energy-…
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    «Linear Algebra and Its Applications» by David & Steven Lay, and Judi McDonald is truly a masterpiece. A textbook teaching Linear Algebra geometrically, application first, with computer exercises and data sets, interactive figures, and projects. 🤩🤩🤩
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    «Introduction to Probability for Data Science» by @stanley_h_chan, with video lectures, exercises, and Python, MATLAB, Julia, R code! 🤩🤩🤩 probability4datascience.com
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    Convolutional Differentiable Logic Gate Networks @FHKPetersen
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    Who on Earth is this?! 😍😍😍 Steven Brunton from @UofWA! me.washington.edu/facultyfinder/… This is absolutely nuts! 🤯🤩🥳 Laplace transform video: youtu.be/7UvtU75NXTg Check him out! The bar keeps rising! I'm in awe 😍 To infinity and beyond! 🚀
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    «Chapter 6» In this chapter, we'll introduce several geometric structures, over which functions are defined, and whose properties can be exploited to reduce computations and ease learning, giving rise to several architecture families we'll cover in this part of the book.
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    «A 2020 Vision of Linear Algebra» six brief videos for teaching and learning linear algebra by… yasss! Him! A 85 years old William Gilbert Strang! ❤️❤️❤️ I hope to have just a fraction of your stamina, dear Gilbert! I’ll try to keep opening eyes!
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    💥 Starting the 2020 edition of @ylecun's Deep Learning class with ~200 students! 🤩 This year we *will* end up with annotated ✏️ video recordings 🎥 and publishable lecture notes 📖, as we're putting the extra effort to renew 🌟 and reorganise 🧐 the material.
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    Let's start the year by brushing up on the basics of neural nets: linear and non-linear transformations. In this episode, we're concerned with inference only. Forward and backwards. We introduce the cost and the energy. 🔋 Website: atcold.github.io/NYU-DLFL22/ youtu.be/QwZQrxIk6Dg
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    Wild how a clown who has never trained a neural net feels entitled to criticise an expert who dedicated his life to pushing this field forward while also teaching all the non-obvious details to newcomers.
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    In «Deep Learning with PyTorch Step-by-Step» @dvgodoy presents a structured, incremental, and from first principles approach to learning PyTorch with beautiful diagrams as if he is having an informal conversation with the reader, with questions and jokes. leanpub.com/pytorch
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    My 13yo middle-schooler explaining to a bunch of PhD students her summer project: estimation of PM2.5 🏭 from daily images 📸 of Beijing, Shanghai, and Phoenix. She compared a classical approach, with engineered feature extractors, to modern deep learning regression. So proud! 🥰
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    «Rich» is a Python library for rich text and beautiful formatting in the terminal. Rich makes it easy to add colour and style to terminal output. It can also render pretty tables, progress bars, markdown, syntax highlighted source code, tracebacks, etc… github.com/willmcgugan/ri…