Nobody wants to spend their day doing hours of busy work. That's why we're starting to see so much about AIOps, or artificial intelligence and machine learning routines that can help to both automate routine tasks and to predict and prevent problems. But we're not yet at the point where you can turn over all of your operations to an AIOps regimen; humans are still involved, and will need to be for the foreseeable future. In this talk, we'll look at what AIOps is, what it will be able to do someday, and how it relates to the intelligent automation we can use today. PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=dD5EXOVdzH4 https://www.youtube.com/watch?v=ttq5LiWiukk

Scroll-based animations used to be pretty hard and usually meant turning to a library. With the Web Animations API and ScrollTimeline, it's now surprisingly easy to do! 🔗 Links ✅ The Polyfill: https://github.com/flackr/scroll-timeline
✅ The Discord community: https://discord.gg/nTYCvrK
✅ Doing this with CSS only (@scroll-timeline): https://youtu.be/mzKfetD9YrA
✅ Intersection Observers: https://youtu.be/T8EYosX4NOo
✅ Bramus' interactive offset visualizer: https://codepen.io/bramus/pen/OJbZbaX
✅ Fantastic article by Bramus on this topic: https://css-tricks.com/scroll-linked-animations-with-the-web-animations-api-waapi-and-scrolltimeline/ ⌚ Timestamps
00:00 – Introduction
00:57 – Creating a scroll tracker – HTML and CSS
02:50 – The polyfill
03:55 – Creating a timeline for the scroll-tracker
06:34 – Attaching the timeline to the scroll-tracker
09:36 – Changing the scrollOffsets
10:20 – Animating only when an element is in the viewport
17:52 – Animating multiple elements
20:41 – Animating when the element is in different locations on the page #css PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=VgS5CP7zlXE https://www.youtube.com/watch?v=ZRCzvK4DnlA

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