Frank Kane, Sundog Education founder and the author of liveVideo course 📼 Machine Learning, Data Science and Deep Learning with Python | http://mng.bz/o27M 📼 takes a deep dive into one of the most powerful machine learning algorithm, eXtreme Gradient Boosting, using a Jupyter notebook with Python. ✔ To learn more about Hyperparameter Tuning and Machine Learning, Data Science and Deep Learning, check out Frank's liveVideo course: Machine Learning, Data Science and Deep Learning with Python | http://mng.bz/o27M "Machine Learning, Data Science and Deep Learning with Python" covers machine learning, Tensorflow, artificial intelligence, and neural networks—all skills that are in demand from the biggest tech employers. Filled with examples using accessible Python code you can experiment with, this complete hands-on data science tutorial teaches you techniques used by real data scientists and prepares you for a move into this hot career path. https://www.youtube.com/watch?v=2KrPbnZEKsw

gccrs is a full alternative implementation of the Rust language ontop of GCC with the goal to become fully upstream with the GNU toolchain. The origin of this project was a community effort several years ago where Rust was still at version 0.9; the language was subject to so much change that it became difficult for a community effort to play catch up. Now that the language is stable, it is an excellent time to create alternative compilers. The developers of the project are keen “Rustaceans” with a desire to give back to the Rust community and to learn what GCC is capable of when it comes to a modern language. PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=chs9LxT9PAg https://www.youtube.com/watch?v=1c4q-93H93Q

This workshop is geared towards anyone who wants to start using Julia. It will be an extremely accessible overview of Julia. You can download Julia here: https://julialang.org/downloads/ PUBLICATION PERMISSIONS:
PyData provided Coding Tech with the permission to republish PyData talks. CREDITS:
PyData YouTube channel: https://www.youtube.com/c/PyDataTV https://www.youtube.com/watch?v=iKm8DbuiqhM