⭕️ BentoML

🔹BentoML is an open-source platform for high-performance ML model serving.

https://github.com/bentoml/BentoML
bentoml/BentoML

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📌Via: @cedeeplearning

#deeplearning #machinelearning
#neuralnetworks #artificial_intelligence

⚪️ Basics of Neural Network Programming

✒️ by prof. Andrew Ng
🔹Source: Coursera

🔖 Lecture 23 Computing Neural Network Output

Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning

#DeepLearning #machinelearning #AI #coursera #free #python #machinelearning #neuralnetworks

⭕️ What are tensors?

Learn from these amazing blogs:

🔹 A Gentle Introduction to Tensors for Machine Learning with NumPy by: Jason Brownlee. https://machinelearningmastery.com/introduction-to-tensors-for-machine-learning/

🔹 WTF is a Tensor?!? by: Matthew Mayo.
https://www.kdnuggets.com/2018/05/wtf-tensor.html

🔹 Quick ML Concepts: Tensors by: Chi Nok Enoch Kan.
https://towardsdatascience.com/quick-ml-concepts-tensors-eb1330d7760f

🔹 Our Instagram post covering this topic: https://www.instagram.com/p/CCSnIO9AVfd/?igshid=a2bgrgoip8zx
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📌Via: @cedeeplearning

#tensor #tensorflow #machinelearning
#neuralnetworks #deeplearninig #tutorial

⭕️ OpenAI’s new language generator GPT-3 is shockingly good—and completely mindless

📌Via: @cedeeplearning


https://www.technologyreview.com/2020/07/20/1005454/openai-machine-learning-language-generator-gpt-3-nlp/

#deeplearning #gp3 #machinelearning #math
#neuralnetworks #AI #MIT

🔹 “Three must know SQL questions to pass your data science interview”
by Jay Feng

Link: https://link.medium.com/dcyr5YtkI7

📌 Via: @cedeeplearning

#sql #datascience #interview #machinelearning
#resume

⚪️ Basics of Neural Network Programming

✒️ by prof. Andrew Ng
🔹Source: Coursera

🔖 Lecture 24 Vectorizing Across Multiple Examples

Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning

#DeepLearning #machinelearning #AI #coursera #free #python #vectorizing #machinelearning #neuralnetworks

⭕️ Fast and Accurate Neural CRF Constituency Parsing

Link on Github: https://github.com/yzhangcs/parser

Paper: https://www.ijcai.org/Proceedings/2020/560
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📌Via: @cedeeplearning

#deeplearning #neuralnetworks

🔹 Facebook built a powerful AI model to simulate entire social media networks in action

⭕️ When it comes to live-fire high-wire acts in the tech industry, there can be few endeavors more daunting than executing a security update to a software platform hosting more than 2.6 billion users.

⭕️ But that’s exactly what Facebook does every time it rolls out an update. Sure, it mitigates the potential for terror by making the changes in batches and conducting an incredible amount of internal testing. But at the end of the day, you never know precisely how any given change could upset the delicate user balance that keeps Facebook on people’s screens.

https://thenextweb.com/neural/2020/07/23/facebook-built-a-powerful-ai-model-to-simulate-entire-social-media-networks-in-action/

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📌Via: @cedeeplearning

#AI #machinelearning #deeplearning
#neuralnetworks #facebook #detection
#prediction

⚪️ Basics of Neural Network Programming

✒️ by prof. Andrew Ng
🔹Source: Coursera

🔖 Lecture 25 Explanation For Vectorized Implementation

Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning

#DeepLearning #machinelearning #AI #coursera #free #python #vectorizing #machinelearning #neuralnetworks

⭕️ How YOLOv5 solved an ambiguity encountered by YOLOv3

To the ones who not might be knowing, a new version of YOLO (You Only Look Once) is here, namely YOLO v5. Many thanks to Ultralytics for putting this repository together.

link: https://towardsdatascience.com/indian-car-license-plate-detection-using-yolo-v5-ae2574578175#4a06-971d24018f84
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📌Via: @cedeeplearning

#deeplearning #YOLO #neuralnetworks #selfdriving #machinelearning

⭕️ AR-Net: A simple autoregressive NN for Time Series


🔹 blog: https://ai.facebook.com/blog/ar-net-a-simple-autoregressive-neural-network-for-time-series/

📕 paper: https://arxiv.org/abs/1911.03118
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📌Via: @cedeeplearning

#timeseries #neuralnetworks #machinelearning #deeplearning

⚪️ Basics of Neural Network Programming

✒️ by prof. Andrew Ng
🔹Source: Coursera

🔖 Lecture 26 Activation Functions

Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning

#DeepLearning #machinelearning #AI #coursera #free #python #math #activation_function #machinelearning #neuralnetworks

⭕️ How You Should Read Research Papers According To Andrew Ng (Stanford Deep Learning Lectures)

Instructions on how to approach knowledge acquisition through published research papers by a recognized figure within the world of machine learning and education

🖊 by Richmond Alake

link: https://towardsdatascience.com/how-you-should-read-research-papers-according-to-andrew-ng-stanford-deep-learning-lectures-98ecbd3ccfb3
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📌Via: @cedeeplearning

#paper #research #stanford #deeplearning #andrew_ng
#neuralnetworks #math #machinelearning

⭕️ Neural Manifold Ordinary Differential Equations

📕 Article: https://arxiv.org/abs/2006.10254

🔹 Github: https://github.com/CUVL/Neural-Manifold-Ordinary-Differential-Equations
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📌Via: @cedeeplearning

⚪️ Basics of Neural Network Programming

✒️ by prof. Andrew Ng
🔹Source: Coursera

🔖 Lecture 27 Why Non-linear Activation Functions

Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning

#DeepLearning #machinelearning #AI #coursera #free #python #math #activation_function #machinelearning #neuralnetworks

📕 Building Machine Learning Powered Applications

Going from Idea to Product Emmanuel Ameisen

📌@cedeeplearning

#book #ML #deeplearning #free #machinelearning

⭕️ DeepMind x UCL | Deep Learning Lectures | 1/12 | Intro to Machine Learning & AI

https://youtu.be/7R52wiUgxZI

📌via: @cedeeplearning

#deepmind #ucl #deeplearning #lecture #AI #machinelearning