Effective Deep Learning Resources: A Shortlist

Jessica YungArtificial Intelligence, Data Science, Education, Machine Learning, Studying

A lot of people ask me how to get started with deep learning. In this post I’ve listed a few resources I recommend for getting started. I’ve only chosen a few because I’ve found precise recommendations to be more helpful. Let me know if you have any comments or suggestions! Prelude: If you’re new to machine learning Deep learning is … Read More

Code, Explained: Training a model in TensorFlow

Jessica YungArtificial Intelligence, Self-Driving Car ND

In a previous post, we went through the TensorFlow code for a multilayer perceptron. Now we will discuss how we train the model with TensorFlow, specifically in a TensorFlow Session. We will use Aymeric Damien’s implementation in this post. I recommend you skim through the code first and have the code open in a separate window. I have included the key portions … Read More

Explaining TensorFlow code for a Multilayer Perceptron

Jessica YungHighlights, Programming, Self-Driving Car ND

In this post we go through the code for a multilayer perceptron in TensorFlow. We will use Aymeric Damien’s implementation. I recommend you have a skim before you read this post. I have included the key portions of the code below. 1. Code Here are the relevant network parameters and graph input for context (skim this):

Here is the model … Read More

Dennis Mortensen, Part 1: Frameworks for looking at the AI Market

Jessica YungData Science, Talk Reviews

dennis-mortensen

Last weekend (24th-25th Sept) was the second Ai.WithTheBest conference – an online conference about artificial intelligence. Over two days, speakers gave talks (often from their homes) with live Q&A. Dennis Mortensen of x.ai kicked off this year’s conference with three frameworks for looking at AI products. He gave two frameworks for looking at the AI market and one framework for … Read More