AI Expert Roadmap

Below you find a set of charts demonstrating the paths that you can take and the technologies that you would want to adopt in order to become a data scientist, machine learning or an AI expert.

What is actually pretty cool is that you can click in any part of roadmap and learn more about mentioned concept!

https://i.am.ai/roadmap/

#ai #artificialintellignece #ml #machinelearning #datascience #roadmap
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Introduction to Machine Learning Problem Framing
By Google

Estimated Course Length: 1 hour

https://developers.google.com/machine-learning/problem-framing

#machinelearning #ml
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ML_cheatsheets.pdf

30 Days of ML, free Kaggle challenge

Machine learning beginner → Kaggle competitor in 30 days.
Non-coders welcome.

Starts August 2nd!

FAQ

I already have some familiarity with Python and/or Machine Learning. Can I still join the program?
Anyone can join! You’ll get more out of the program if you’re not a very advanced Python user, or if you are relatively new to machine learning.

What is the time commitment for the program?
Assignments should take about 1 hour/day to complete.

How much is the program?
Nothing! All you need is a Kaggle account.

Do I need to bring my own GPU or deep learning workstation?
No, Kaggle provides free hosted notebooks with access to GPUs and TPUs to complete your data science projects.

🔗 https://www.kaggle.com/thirty-days-of-ml

Sign Up for the challenge.

#kaggle #python #machinelearning #ml
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Graph Neural Networks: Algorithms and Applications

A great presentation by Jian Tang about GNN basics, training many layers, self-supervised learning and statistical relational learning.

Neural Networks and Deep Learning, a free online book.

The book will teach you about:

* Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data
* Deep learning, a powerful set of techniques for learning in neural networks

http://neuralnetworksanddeeplearning.com/index.html

InsightFace: 2D and 3D Face Analysis Project

Good implementation for face recognition, and landmark detection
ArcFace, CosFace, SubCenter-ArcFace, VPL, Partial-FC

https://github.com/deepinsight/insightface

CS109 Data Science
By Harvard University

⌛️ 12 weeks
✅ Video lectures
✅ Slides
✅ Lab exercises

🔗 http://cs109.github.io/2015/pages/videos.html

Note: i have issues with first video link but others are fine.

#datascience #pyton #harvard
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Graph ML in Industry Workshop

When I wrote top applications of GNNs at the beginning of this year, I had a feeling that graph ML community is mature enough to start being used in industrial companies. Nine months ahead we decided to gather researchers, engineers, and industry professionals to talk about applications of graphs in the companies. Please, join us on 23rd Sept, 17-00 Paris time (free, online, ~3 hours) by registering at the link.

Learning From Data
Free course by Caltech - California Institute of Technology

✅ 23 sections with pdf slides and video lessons

https://work.caltech.edu/library/

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Four Deep Learning Papers to Read in September 2021

‘Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning’

Authors: Feurer et al. (2021)
📝 Paper
🤖 Code


‘How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers’

Authors: Steiner et al. (2021)
📝 Paper
🤖 Code


‘Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization’

Authors: Jastrzebski et al. (2021)
📝 Paper


‘Do Vision Transformers See Like Convolutional Neural Networks?’

Authors: Raghu et al. (2021)
📝 Paper

Source: Medium

Reinforcement Learning Lecture Series 2021

🎬 13 lessons
⏰ 14 hours

Taught by DeepMind researchers, this series was created in collaboration with University College London (UCL) to offer students a comprehensive introduction to modern reinforcement learning.

https://deepmind.com/learning-resources/reinforcement-learning-series-2021

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Deep learning at Oxford 2015

🎬 16 lessons
⏰ 15 hours

https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu

#deeplearning #oxford
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The People + AI Guidebook by Google

The People + AI Guidebook is a set of methods, best practices and examples for designing with AI.


https://pair.withgoogle.com/guidebook/

Get ready for second annual #NLPSummit by John Snow Labs.

Week One comes with 50+ unique sessions with a special track on #NLP in #Healthcare.
Week Two - beginner to advanced training workshops with certification.
Hear from industry leaders at NASA, Vonage, Zillow, Merck, Amazon, Walmart Labs, Booz Allen Hamilton, Morgan Stanley, Salesforce, Roku, Zillow and many more!
Free registration: https://www.nlpsummit.org/2021-events/
#ML #AI #digitalhealthcare #dataengineer #deeplearning

Mathematics for Machine Learning

Published by Cambridge University Press (published April 2020)

https://mml-book.com
PDF: https://mml-book.github.io/book/mml-book.pdf