Introduction to Machine Learning Model Interpretation
Regardless of what problem you are solving an interpretable model will always be preferred because both the end-user and your boss/co-workers can understand what your model is really doing.
Regardless of what problem you are solving an interpretable model will always be preferred because both the end-user and your boss/co-workers can understand what your model is really doing.
Learn how to create your own object detector using the Tensorflow Object Detection API.
Get started visualizing data in Python using Matplotlib, Pandas and Seaborn
Learn the basics of Keras, a high-level library for creating neural networks running on Tensorflow.
Scrape data from Reddit using PRAW, the Python wrapper for the Reddit API.
Build a system that is able to recommend books to users depending on what books they have already read using the Keras deep learning library.
Generating text in the style of Sir Arthur Conan Doyle using a RNN
Gilbert Tanner is a robotics researcher and Bachelor student at the University of Klagenfurt.
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