Pandas can be tricky, and there is a lot of bad advice floating around. This talk will cut through some of the biggest issues I've seen with Pandas code after working with the library for a while and writing two books on it. Do you struggle writing Pandas code? Do you spend too much time trying to understand code that you have previously written? Would you like to write code that your colleagues can easily understand and use? Our speaker, Matt Harrison, has been using Python since 2000. He runs MetaSnake, which provides corporate training for Python and Data Science. He is the author of Machine Learning Pocket Reference, the bestselling Illustrated Guide to Python 3, and Pandas Cookbook 1.x, among other books. PUBLICATION PERMISSIONS:
PyData provided Coding Tech with the permission to republish PyData talks. CREDITS:
PyData YouTube channel: https://www.youtube.com/channel/UCOjD18EJYcsBog4IozkF_7w https://www.youtube.com/watch?v=UURvPeczxJI

Frank Kane, Sundog Education founder and the author of liveVideo course 📼 Machine Learning, Data Science and Deep Learning with Python | http://mng.bz/gggR 📼 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/gggR "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=0ikyjpaUDFQ

Web technologies have come leaps and bounds. But are you still using the tired old database from last generation? Let’s look at the methodology of microservices, compare it to bounded contexts, and look at ops tasks for micro-databases. Let’s tour all the flavors of databases, understand their pros and cons, and when you would choose it. You’ll leave with a roadmap for moving from data-monolyth to micro-databases. PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=jTCBVR2Qtzo ***
Most Famous Athletes in The World: https://www.youtube.com/watch?v=hLQX3bNhx1Q https://www.youtube.com/watch?v=-9Veoch50Bg