Data science/ML/AI

🔗 Book link #machinelearning #ml #datascience ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @coding_interview_preparation for more. *This channel belongs to @bigdataspecialist group

The Periodic Table Of Data Science

Deep Learning Do It Yourself! This site collects resources to learn Deep Learning in the form of Modules available through the sidebar on the left. https://dataflowr.github.io/website/ ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

Graph ML and deep learning courses This is another post on your request. Other courses you requested will be shared in following days. Geometric Deep learning course AMMI21 👨‍🏫 Teachers: Michael M. Bronstein, Joan Bruna, Taco Cohen, Petar Veličković 📚12 lectures, 2 tutorials, and 4 seminars This course follows GDL BOOK 🔗 Course link: https://geometricdeeplearning.com/lectures/ Machine Learning for Graphs and Sequential Data (MLGS) by Stephan Günnemann Awesome course covering in depth generative models, robustness, sequential data, clustering, label propagation, GNNs, and more 🔗 Course link: https://www.in.tum.de/daml/teaching/mlgs/ Stanford CS224W course on graph ML A legendary Stanford CS224W course on graph ML now releases videos on YouTube for 2021 🎬 60 Videos ⏰ 30h 🔗 Course link Python For Data Science (Udemy) This course specifically created for Data Science / AI / ML / DL. It covers BASICS PYTHON ONLY Rating ⭐️: 4.1 out of 5 Students 👨‍🎓: 65,523 students Duration ⏰: 3hr 55min of on-demand video 🔗 Course link Deep Learning Prerequisites: The Numpy Stack in Python V2 (Udemy) Rating ⭐️: 4.6 out of 5 Students 👨‍🎓: 34,785 Duration ⏰: 1hr 59min of on-demand video 🔗 Course link There is also this cool blogpost by Gordić Aleksa: How to get started with Graph Machine Learning And one early access version book: Graph Powered Machine Learning by: Allesandro Negro 🔗 Book link #graphML #ML #machinelearning #deeplearning #python ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ 👉Join @bigdataspecialist for more👈

Rules of Machine Learning: Best Practices for ML Engineering Author: Martin Zinkevich This document is intended to help those with a basic knowledge of machine learning get thebenefit of best practices in machine learning from around Google. 👉 43 ML Rules to follow 🔗 http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

Machine Learning for Healthcare (Spring 2019) By Massachusetts Institute of Technology (MIT) 🎬 25 video lessons ⏰ 33 hours 👨‍🏫 Prof. Peter Szolovits 👨‍🏫 Prof. David Sontag https://www.classcentral.com/course/mit-opencourseware-machine-learning-for-healthcare-spring-2019-40955/classroom #ml #machinelearning #healthcare #MIT ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

ML and NLP Research Highlights of 2021 by Sebastian Ruder This post summarizes progress across multiple impactful areas in ML and NLP in 2021. Contents: Universal Models Massive Multi-task Learning Beyond the Transformer Prompting Efficient Methods Benchmarking Conditional Image Generation ML for Science Program Synthesis Bias Retrieval Augmentation Token-free Models Temporal Adaptation The Importance of Data Meta-learning https://ruder.io/ml-highlights-2021/ ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool DS/ML materials.

Free 10-Hour Machine Learning Course by freecodecamp Section 1: Basics of Machine Learning Section 2: Linear Regression & Regularization Section 3: Logistic Regression & Performance Metrics Section 4: Support Vector Machine Section 5: PCA Section 6: Learning Theory Section 7: Decision Trees & Random Forest Section 7.5: Learning more algorithms and building more projects Section 8: Unsupervised Learning Algorithms Section 9: Building Applications 🔗 Course link: https://www.freecodecamp.org/news/free-machine-learning-course-10-hourse/ 10-hour youtube video: https://www.youtube.com/watch?v=NWONeJKn6kc ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool DS/ML materials.

Data Science: Python for Data Analysis 2022 Full Bootcamp Rating ⭐️: 4.3 out of 5 Students 👨‍🏫: 104,287 Created by: Ahmed Ibrahim and SDE OCTOPUS | AI 🔗 Course link Note: Free coupon is inserted in URL. Number of free spots is limited to 1000. Once this number is reached, coupon won't be valid anymore. #python #datanalysis #datascience ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

Introduction to Data Science by University of Washington 🎬 95 video sessions ⏰ Duration: 16h 👨‍🏫 Instructor: Bill Howe, PhD ✅ Completely free 🔗 Course link #datascience #ds #ml #washingtonuniversity ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ 👉Join @bigdataspecialist for more👈

Introduction to Machine Learning (Fall 2020) By Massachusetts Institute of Technology, MIT Length: 13 weeks 🔗 Course link #ml #machinelearning #datascience #MIT ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

Neural Networks with JavaScript Succinctly 🔗 Book PDF #javascript #datascience #neuralnetworks ➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @programming_books_bds for more

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

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

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/

Deep learning at Oxford 2015 🎬 16 lessons ⏰ 15 hours https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu #deeplearning #oxford ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

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 ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

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

Learning From Data Free course by Caltech - California Institute of Technology ✅ 23 sections with pdf slides and video lessons https://work.caltech.edu/library/ 👉 Join @datascience_bds and @bigdataspecialist for more

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.