Understanding and being able to justify what your machine learning model has learned is very important.

In this post, I cover :

• understanding model by their weights
• understanding how individiual feature interact through partial dependency plots
• justifying individual predictions using Shap and Lime

Google Cloud had their annul conference in April this year in San Francisco. There were a lot of cool announcements.

Here is my list of announcements that I am excited for.

On March, I attended the machine learning conferene ML Conf in NYC.

Here are links shared from the conferences:

• Slides
• [Book Discount (40%)](https://mlconf.com/blog/ tweet-for-a-chance-to-win-free-books-at-mlconf-nyc-this-friday/) ctwmlconfny19
• Speaker Resources
• Videos

Here are a list of my favorite talks.