FREE NLP Course
NLP Course | For You - interactive lectures-blogs, research thinking exercises and related papers with summaries. And fun! These are not just course materials - this is something developed specially for you
https://lena-voita.github.io/nlp_course.html
NLP Course | For You - interactive lectures-blogs, research thinking exercises and related papers with summaries. And fun! These are not just course materials - this is something developed specially for you
https://lena-voita.github.io/nlp_course.html
Deep Learning with Pytorch by Prof.Yann LeCun (CNN Founder)
This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition.
GitHub Link: https://atcold.github.io/pytorch-Deep-Learning/
YouTube Playlist: https://www.youtube.com/playlist?list=PLLHTzKZzVU9eaEyErdV26ikyolxOsz6mq
This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition.
GitHub Link: https://atcold.github.io/pytorch-Deep-Learning/
YouTube Playlist: https://www.youtube.com/playlist?list=PLLHTzKZzVU9eaEyErdV26ikyolxOsz6mq
YouTube
NYU Deep Learning SP20
Course website: http://bit.ly/DLSP20-web
Nvidia acquires ARM for $40Billion
https://nvidianews.nvidia.com/news/nvidia-to-acquire-arm-for-40-billion-creating-worlds-premier-computing-company-for-the-age-of-ai?ncid=so-face-68622#cid=gnl_so-face_en-us
https://nvidianews.nvidia.com/news/nvidia-to-acquire-arm-for-40-billion-creating-worlds-premier-computing-company-for-the-age-of-ai?ncid=so-face-68622#cid=gnl_so-face_en-us
NVIDIA Newsroom
NVIDIA to Acquire Arm for $40 Billion, Creating World’s Premier Computing Company for the Age of AI
NVIDIA and SoftBank Group Corp. today announced a definitive agreement under which NVIDIA will acquire Arm Limited from SBG and the SoftBank Vision Fund in a transaction valued at $40 billion.
Learn Python, Break Python
A Beginner's introduction to Programming
Learn Python, Break Python is a hands-on introduction to the Python programming language, written for people who have no experience with programming whatsoever. Hey, we all have to start somewhere. As such, the examples and teaching style used in this text make absolutely no expectations about your prior programming experience. If you've never used a programming language before, leaping into Python might seem a bit scary at first. You don't need to worry. Learning how to program a computer is far from impossible. Anyone can pick up the art of programming with a little time and a bit of patience.
👉 Grab your free eBook access from here
A Beginner's introduction to Programming
Learn Python, Break Python is a hands-on introduction to the Python programming language, written for people who have no experience with programming whatsoever. Hey, we all have to start somewhere. As such, the examples and teaching style used in this text make absolutely no expectations about your prior programming experience. If you've never used a programming language before, leaping into Python might seem a bit scary at first. You don't need to worry. Learning how to program a computer is far from impossible. Anyone can pick up the art of programming with a little time and a bit of patience.
👉 Grab your free eBook access from here
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Mathworks Deep learning workflow: tips, tricks, and often forgotten steps
Getting started in deep learning – and adopting an organized, sustainable, and reproducible workflow – can be challenging. This is a highly interactive and iterative process which consists, to a certain degree, in working on a trial-and-error basis (but not quite… there is a "method to the madness").
https://www.kdnuggets.com/2020/09/mathworks-deep-learning-workflow.html
Getting started in deep learning – and adopting an organized, sustainable, and reproducible workflow – can be challenging. This is a highly interactive and iterative process which consists, to a certain degree, in working on a trial-and-error basis (but not quite… there is a "method to the madness").
https://www.kdnuggets.com/2020/09/mathworks-deep-learning-workflow.html
KDnuggets
MathWorks Deep learning workflow: tips, tricks, and often forgotten steps - KDnuggets
Getting started in deep learning – and adopting an organized, sustainable, and reproducible workflow – can be challenging. This blog post will share some tips and tricks to help you develop a systematic, effective, attainable, and scalable deep learning workflow…
Research Paper on NumPy🥳
https://www.nature.com/articles/s41586-020-2649-2
https://www.nature.com/articles/s41586-020-2649-2
Nature
Array programming with NumPy
Nature - NumPy is the primary array programming library for Python; here its fundamental concepts are reviewed and its evolution into a flexible interoperability layer between increasingly...
Python Data Science Handbook
This one contains the full text of the Python Data Science Handbook by Jake VanderPlas; the content is available on GitHub in the form of Jupyter notebooks. which is well structured and useful for learning Data Science. Beginners friendly
https://jakevdp.github.io/PythonDataScienceHandbook/
This one contains the full text of the Python Data Science Handbook by Jake VanderPlas; the content is available on GitHub in the form of Jupyter notebooks. which is well structured and useful for learning Data Science. Beginners friendly
https://jakevdp.github.io/PythonDataScienceHandbook/
GitHub
GitHub - jakevdp/PythonDataScienceHandbook: Python Data Science Handbook: full text in Jupyter Notebooks
Python Data Science Handbook: full text in Jupyter Notebooks - jakevdp/PythonDataScienceHandbook
Most Machine Learning articles on Medium are really very bad quality and repetitive. Titles are usually clickbaits. Most start with a story which is utter nonsense and totally not required. In some 5-10% content is useful but most are fully useless. Sorry if I hurt feelings. Credits: Abhishek Thakur, Kaggle Grandmaster
Agree👍 or hearted😢
Agree👍 or hearted😢
AI/DL Certificates: No one cares about certificates in our business. Period. If you learn something while you get the certificate, sure. Get one print out and post it on your wall then. It does make an office less boring.
AI/DL Degrees: If you do interesting projects, and you gain understanding and skills out of the projects, then an AI degree is good for you. Otherwise, no one cares about your degrees. What about a PhD or a master? That depends on the quality of your publications, see below.
AI/DL Projects: If you actually do the projects, but not copying from "10-lines to do object detection" you see on-line, and you actually understand the principles of the techniques you are using, then those projects would be great experience for you. Otherwise, no one cares if you had done 1000 projects in your life.
AI/DL Publications: If the writing process makes you think of a novel technique in the field, absolutely! Or you gain fundamental understanding of a class of algorithms when you research the background, sure that matters a lot! That's why graduates who has past publications are usually strong candidates for many big companies ML department. (Make sure you can answer questions about your own publication though!)
AI/DL Blog Posts You Write: If the quality of the blog is like a paper, sure. But if you just copy from "10-lines to do object detection" , no one cares.
Great Programming Skill: If that means you have source-level understanding of a major deep learning framework, wooooh, I would love to see your resume! What if you know 7 different ways to do string manipulation in python? That certainly is an interesting programming skill, but programming skill does not equal to ML skill. So again, no one cares.
In a nutshell, what matters most is whether you genuinely understand the field. Credits: Arthur Chan
AI/DL Degrees: If you do interesting projects, and you gain understanding and skills out of the projects, then an AI degree is good for you. Otherwise, no one cares about your degrees. What about a PhD or a master? That depends on the quality of your publications, see below.
AI/DL Projects: If you actually do the projects, but not copying from "10-lines to do object detection" you see on-line, and you actually understand the principles of the techniques you are using, then those projects would be great experience for you. Otherwise, no one cares if you had done 1000 projects in your life.
AI/DL Publications: If the writing process makes you think of a novel technique in the field, absolutely! Or you gain fundamental understanding of a class of algorithms when you research the background, sure that matters a lot! That's why graduates who has past publications are usually strong candidates for many big companies ML department. (Make sure you can answer questions about your own publication though!)
AI/DL Blog Posts You Write: If the quality of the blog is like a paper, sure. But if you just copy from "10-lines to do object detection" , no one cares.
Great Programming Skill: If that means you have source-level understanding of a major deep learning framework, wooooh, I would love to see your resume! What if you know 7 different ways to do string manipulation in python? That certainly is an interesting programming skill, but programming skill does not equal to ML skill. So again, no one cares.
In a nutshell, what matters most is whether you genuinely understand the field. Credits: Arthur Chan
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Introduction to Deep Learning
MIT's official introductory course on deep learning methods with applications in Computer Vision, NLP, Medicine, robotics, and more!
http://introtodeeplearning.com/
MIT's official introductory course on deep learning methods with applications in Computer Vision, NLP, Medicine, robotics, and more!
http://introtodeeplearning.com/
MIT Deep Learning 6.S191
MIT's introductory course on deep learning methods and applications
CNN Explainer
Learn Convolutional Neural Network (CNN) in your browser!
https://poloclub.github.io/cnn-explainer/
Learn Convolutional Neural Network (CNN) in your browser!
https://poloclub.github.io/cnn-explainer/
Made with ML Topics
Your one-stop platform to explore, learn and build all things machine learning.This page is for the best resources of all time by topic.
https://madewithml.com/topics/
Your one-stop platform to explore, learn and build all things machine learning.This page is for the best resources of all time by topic.
https://madewithml.com/topics/
Here is awesome collection of computer vision pre-trained models.
https://github.com/balavenkatesh3322/CV-pretrained-model
https://github.com/balavenkatesh3322/CV-pretrained-model
GitHub
GitHub - balavenkatesh3322/CV-pretrained-model: A collection of computer vision pre-trained models.
A collection of computer vision pre-trained models. - balavenkatesh3322/CV-pretrained-model
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Some Notable Recent ML Papers and Future Trends by Aran Komatsuzaki, here is the link
Aran Komatsuzaki
Some Notable Recent ML Papers and Future Trends
I have aggregated some of the notable papers released recently, esp. ICLR 2021 submissions, with concise summaries, visualizations and my comments. The development in each field is summarized, and …
PyTorch announced First PyTorch Developer Day starting 8 AM on November 12, 2020 PST. Learn more:
https://pytorch.org/blog/pytorch-developer-day-2020/
https://pytorch.org/blog/pytorch-developer-day-2020/
PyTorch
Announcing PyTorch Developer Day 2020
Starting this year, we plan to host two separate events for PyTorch: one for developers and users to discuss core technical development, ideas and roadmaps called “Developer Day”, and another for the PyTorch ecosystem and industry communities to showcase…
Last Friday, Google announced the support of its AutoML algorithm for time series forecasting. According to the announcement, this cloud-based ML forecasting algorithm is fully automated that neither needs feature engineering nor tunning, with high-quality results.
This is come just four days after the Facebook announcement on their deep learning forecasting model - NeuralProphet. It is interesting to see this trend of moving toward ML/DL solutions for time series forecasting. ~Rami Krispin
More details available here: https://ai.googleblog.com/2020/12/using-automl-for-time-series-forecasting.html
This is come just four days after the Facebook announcement on their deep learning forecasting model - NeuralProphet. It is interesting to see this trend of moving toward ML/DL solutions for time series forecasting. ~Rami Krispin
More details available here: https://ai.googleblog.com/2020/12/using-automl-for-time-series-forecasting.html
research.google
Using AutoML for Time Series Forecasting
Posted by Chen Liang and Yifeng Lu, Software Engineers, Google Research, Brain Team Time series forecasting is an important research area for machi...
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Why PyTorch?
https://www.infoworld.com/article/3597904/why-enterprises-are-turning-from-tensorflow-to-pytorch.html
https://www.infoworld.com/article/3597904/why-enterprises-are-turning-from-tensorflow-to-pytorch.html
InfoWorld
Why enterprises are turning from TensorFlow to PyTorch
The deep learning framework PyTorch has infiltrated the enterprise thanks to its relative ease of use. Three companies tell us why they chose PyTorch over Google’s renowned TensorFlow framework.
MIT has launched a new FREE course on Machine Learning!
Link to enroll: http://bit.ly/3acnayN
Link to enroll: http://bit.ly/3acnayN
Harvard University has this Free course on Data Science : Machine Learning!
Link to enroll : http://bit.ly/2WtDPFZ
Link to enroll : http://bit.ly/2WtDPFZ