Artificial Intelligence && Deep Learning
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Channel for who have a passion for -
* Artificial Intelligence
* Machine Learning
* Deep Learning
* Data Science
* Computer vision
* Image Processing
* Research Papers

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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.

πŸ‘‰@DeepLearning_AIπŸ‘ˆ

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

πŸ‘‰ @DeepLearning_AIπŸ‘ˆ

https://ai.facebook.com/blog/using-neural-networks-to-solve-advanced-mathematics-equations/
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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/
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3D Face Reconstruction with Position Map Regression Networks
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
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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.
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Deep Learning for Object Detection: A Comprehensive Review

* Single Shot Multibox Detector (SSD) with MobileNets

* SSD with Inception V2

* Region-Based Fully Convolutional Networks (R-FCN) with Resnet 101

* Faster RCNN with Resnet 101

* Faster RCNN with Inception Resnet v2

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2.https://towardsdatascience.com/deep-learning-for-object-detection-a-comprehensive-review-73930816d8d9