Autoencoders and PCA - Githubissues

Abstract (2-3 lines) Autoencoders are one of the generative models. They work on unsupervised algorithm. Autoencoders are mainly used for dimensionality reduction , image denoising , image generation and also recommendation systems.
Brief Description and Contents to be covered I would be covering the following topics : -> Dimensionality Reduction Problem -> PCA -> Autoencoders -> Latent Space -> PCA vs Autoencoders -> Types of Autoencoders -> Applications of Autoencoders -> Implementation : Image Denoising of Facial Images Dataset using Autoencoders
Pre-requisites for the talk
Basic concepts of Neural Networks should be clear
Basic knowledge of python and Keras is also required.
Time required for the talk 60 - 70 mins
Link to slides https://bit.ly/DLQAutoencoders
Will you be doing hands-on demo as well? Yes
Link to ipython notebook (if any) https://bit.ly/Autoencoders
About yourself I am currently pursuing B.Tech in CS , 3rd year at NIT Kurukshetra. I am an AI enthusiast. Also last year , I had done a deep learning internship after which I was selected as Google AI Explore ML Facilitator due to which I had taken 10 sessions in my college which was attended by over 250 students where I had taught them various ML and DL concepts. Also recently during Quarantine times , I have been taking Deep Learning and Computer Vision webinars. Currently I am doing a 6 month internship as a DLCV intern at Nayan Technologies which is one of the leading startups and has collabration with Dubai Police. Also I was recently selected by Omdena as a Junior ML Engineer where I would be working on analysing the domestic violence and online harrasment trends during COVID-19. I have also written a research paper on Multimodal Emotion Recognition which I would be submitting for publication in one of the conferences.
Are you comfortable if the talk is recorded and uploaded to PyData Delhi's YouTube channel ? Yes Sure.
Any query ? No

pydatadelhi / talks

Autoencoders and PCA #129