Frequently Asked Questions (FAQ)
Who is the Intended Audience?
The intended audience for this podcast series is the general public and the intended objective of this podcast series is to help popularize and de-mystify the field of Artificial Intelligence by explaining fundamental concepts in an entertaining manner.
However, many advanced topics in artificial intelligence and machine learning will be discussed at a “high-level” so students, scientists, and engineers working in the area of machine learning may find this podcast series beneficial for identifying relevant “entry points” into very advanced topics in statistical machine learning. Relevant references to advanced readings are provided (when applicable) in the show notes for each episode.
Why should I submit a review to ITUNES or STITCHER? Why is this important?
Although I do not know for sure, it is likely that both ITUNES and STITCHER use machine learning algorithms which increase the likelihood the show LEARNING MACHINES 101 appears in search results based upon the reviews of the shows received. Thus, your review will be extremely helpful in reaching my goal of distributing the content of this show to the general public. You can submit a review of LEARNING MACHINES 101 to either ITUNES or STITCHER by visiting the links: www.learningmachines101.com/itunes and www.learningmachines101.com/stitcher.
Can I listen to the Episodes in any Order that I choose?
Although each episode is intended to be self-contained, listening to the episodes in the order in which they are presented is highly recommended. Start at Episode 1 and continue listening!
How often are new Episodes released?
A new episode of Learning Machines 101 will be released on the third Monday of every month.
Each episode will be approximately 20-35 minutes in length.
What are Categories and Tags?
The concept of a “category” and the concept of a “tag” are used in a very specific way on this website. One way to visualize the concept of a “category” (for this website) is that is specifies the “table of contents” of this website. Different categories correspond to different topics which will be considered and the topic structure is hierarchical in nature. On the other hand, a “tag” (for this website) is analogous to the “index” in a book. Categories tend to be more author-oriented while tags tend to be more reader-oriented. You can search for blogs on related topics using a category search or a tag search!