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Introduction to Deep Learning (CMU)

-Person Venue: Giant Eagle Auditorium, Baker Hall (A51) “Deep Learning” systems, typified by deep neural networks, are increasingly taking over all the AI tasks, ranging from language understanding, speech and image recognition, to machine translation, planning, and even game playing and autonomous driving. As a result, expertise in deep learning is fast changing from an esoteric desirable to a mandatory prerequisite in many advanced academic settings, and a large advantage in the industrial job market.

Kateryna Shapovalenko: kshapova@andrew.cmu.edu Miya Sylvester: nsylvest@andrew.cmu.edu Alexander Moker: amoker@andrew.cmu.edu Purusottam Samal: psamal@andrew.cmu.edu Shravanth Srinivas: shravans@andrew.cmu.edu Yuzhou Wang: yuzhouwa@andrew.cmu.edu Massa Baali: mbaali@andrew.cmu.edu Vedant Singh: vhsingh@andrew.cmu.edu Sadrishya Agrawal: sadrisha@andrew.cmu.edu Michael Kireeff: mkireeff@andrew.cmu.edu Vishan Oberoi: voberoi@andrew.cmu.edu Ishita Gupta: ishitag@andrew.cmu.edu Shubham Kachroo: skachroo@andrew.cmu.edu Shrey Jain: shreyj@andrew.cmu.edu Floris Nzabakira: fnzabaki@andrew.cmu.edu Christine Muthee: cmuthee@andrew.cmu.edu Ahmed Issah: aissah@andrew.cmu.edu Shubham Singh: shubham4@andrew.cmu.edu Tanghang Elvis Tata: etanghan@andrew.cmu.edu John Liu: johnliu@andrew.cmu.edu Damilare Olatunji: dolatunj@andrew.cmu.edu Brian Ebiyau: bebiyau@andrew.cmu.edu Peter Wauyo: pwauyo@andrew.cmu.edu Eman Ansar: eansar@andrew.cmu.edu Slides (PDF)MediaServicesYoutube Momentum, Polyak (1964) Nestorov (1983)Derivatives and Influences Quiz 4 8Wednesday, Feb 5 Training Part VI Optimizers and Regularizers Choosing a Divergence (Loss) Function Batch Normalization Dropout Slides (PDF)MediaServicesYoutubeDerivatives and Influence Diagrams ADAGRAD, Duchi, Hazan and Singer (2011)Adam: A method for stochastic optimization, Kingma and Ba (2014) 9Monday, Feb 10 Shift Invariance Convolutional Neural Networks (CNNs) - Part I

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