Implementing deep learning algorithms require knowledge of various DL libraries, how to interface outside files or streaming data to it, along with tuning all sorts of parameters. Deep Learning also does not give you much explanation on what features contribute to a model working well. Jorge Torres discusses MindsDB, a new framework for AutoML that simplifies implementation of neural network models for researchers, along with providing explanation of features. Sponsors

• Machine Learning for Software Engineers by Educative.io
• CacheFly

Panel

• Charles Max Wood
• Gant Laborde

Guest

• Jorge Torres

Links

• www.mindsdb.com
• pytorch.org
• tensorflow.org
• www.geeksforgeeks.org/confusion-matrix-machine-learning
• www.pyimagesearch.com/2020/02/17/autoencoders-with-keras-tensorflow-and-deep-learning
• https://www.kiwibot.com/

Picks Gant Laborde:

• NVIDIA RTX Voice: Setup Guide

Charles Max Wood:

• Russell Brunson’s books

Jorge Torres:

• Iain M. Banks, Author on Amazon
• krisp.ai

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