Best of Machine Learning in 2019: Reddit Edition

A look at 17 of the most popular projects, research papers, demos, and more from the subreddit r/MachineLearning over the past year

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https://heartbeat.fritz.ai/best-of-machine-learning-in-2019-reddit-edition-5fbb676a808

CS221: Artificial Intelligence: Principles And Techniques | Stanford University

What do web search, speech recognition, face recognition, machine translation, autonomous driving, and automatic scheduling have in common? These are all complex real-world problems, and the goal of artificial intelligence (AI) is to tackle these with rigorous mathematical tools.

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https://www.newworldai.com/cs221-artificial-intelligence-principles-and-techniques-stanford-university/

Using neural networks to solve advanced mathematics equations

Facebook AI has built the first AI system that can solve advanced mathematics equations using symbolic reasoning. By developing a new way to represent complex mathematical expressions as a kind of language and then treating solutions as a translation problem for sequence-to-sequence neural networks.

January 14,2020

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https://ai.facebook.com/blog/using-neural-networks-to-solve-advanced-mathematics-equations/

Lecture Notes: Regularization for Deep Learning

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https://towardsdatascience.com/lecture-notes-regularization-be3e7f8e7749

Intro to anomaly detection with OpenCV, Computer Vision, and scikit-learn 👉(with source code)

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https://www.pyimagesearch.com/2020/01/20/intro-to-anomaly-detection-with-opencv-computer-vision-and-scikit-learn/

StarGAN v2: Diverse Image Synthesis for Multiple Domains

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https://arxiv.org/abs/1912.01865

Un-official TensorFlow Implementation https://github.com/clovaai/stargan-v2

In today’s brand new tutorial you will learn how to utilize YOLO and Tiny-YOLO for near real-time object detection on the Raspberry Pi with a Movidius NCS (with source code):

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https://www.pyimagesearch.com/2020/01/27/yolo-and-tiny-yolo-object-detection-on-the-raspberry-pi-and-movidius-ncs/

Real-time and video processing object detection using Tensorflow, OpenCV and Docker.

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https://towardsdatascience.com/real-time-and-video-processing-object-detection-using-tensorflow-opencv-and-docker-2be1694726e5

Face Estimation

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Dataset :- https://domedb.perception.cs.cmu.edu/

Code:- https://github.com/CMU-Perceptual-Computing-Lab/openpose

It doesn’t matter if you are beginner or new to machine learning or advanced researcher in the field of deep learning methods and their application, everybody can benefit of Lex Fridman’s course on Deep Learning for Self-Driving Cars.

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https://www.newworldai.com/deep-learning-and-self-driving-cars-from-mit-lectures-01-05/?fbclid=IwAR1hxhjsHMihuDNyBvA8zycdPKv6anSkkkpGws3LKsumcdntoVTvQhp8slU

3D Face Reconstruction with Position Map Regression Networks 👉 (with source code)

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2. https://heartbeat.fritz.ai/3d-face-reconstruction-with-position-map-regression-networks-36f0ac2d3ef1

3. https://github.com/YadiraF/PRNet

FREE ONLINE COURSES

Browse the latest free online courses from HARVARD University including "CS50's Introduction to Game Development", "CS50's Web Programming with Python and JavaScript" , "CS50's Mobile App Development with React Native" and so on....

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2. https://online-learning.harvard.edu/catalog/free

CS230 Deep Learning Lectures | Stanford Engineering

Deep Learning is one of the most highly sought after skills in AI. In this course, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more.

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2. https://www.newworldai.com/cs230-deep-learning-stanford-engineering/?fbclid=IwAR2BXdgS70N5wVeTdnevVL4eF_L3_l67vBetQkCOIoEazDZLeSx5TJUp6t0

Good day dear subscribers.
Within this past a year we learn or still learning more about specific topics through channel.
I try with my best to provide, keep going with contemporary knowladge and practice, as well as, keep in touch with things based on #AI, #ML, #DL, #DS, #Python.
Thanks for being with us and Stay with us.