The Autodidact's Register: Issue #1

The World Wide Web houses the greatest library ever known to man. This metaphorical libary is chock full of all kinds of resources one needs to acquire skills and knowledge. Naval Ravikant puts it succintly ⁠⁠⁠— "The internet is the best school ever created. The best peers are on the Internet. The best books are on the Internet. The best teachers are on the Internet. The tools for learning are abundant. It’s the desire to learn that’s scarce."

However, the sheer volume of information available on the web makes cataloguing resources a challenging task. After bookmarking hundreds of articles, podcast episodes, tweets, videos etc., I've realized that I rarely visit these resources for a second ⁠⁠⁠⁠time ⁠⁠⁠— which is something I know I should be doing. Hell, even bookmarking amazing tweets doesn't seem to be of any fruitful purpose, as they eventually get buried in the list of favorites. Same goes for great blog posts, articles and other kinds of media. Hence, I've decided to create digests of resources from which I learn from, both for my own reference, and for others who might find this information useful. I'm calling this series of digests "The Autodidact's Register". This is the first issue.

Table of Contents


Podcasts

This issue's podcasts feature guests that work in technology, venture capital, gaming, and stand-up comedy.

Behind The Tech with Kevin Scott: Andrew Ng

Kevin Scott talks with Andrew Ng about the Google Brain project, Coursera, Baidu and Ng’s most recent project, deeplearning.ai.

Listen

DataFramed: Lukas Vermeer

Online experiments, data science and product development at Booking.com.

Listen

TWiML Talk: Soumith Chintala

Sam and Soumith discuss the market evolution of deep learning frameworks and tools.

Listen

TWiML Talk: Jeremy Howard

Sam discusses fastai ⁠⁠⁠— the course and the libary ⁠⁠⁠— with the creator himself: Jeremy Howard.

Listen

Talk Python: David Lord

Michael and David dive into the new features of Flask as well as the future directions for it.

Listen

The Joe Rogan Experience: Naval Ravikant

One of the greatest JRE episodes ever recorded. I even wrote a summary of key takeaways from this episode here.

Listen

IGN Unfiltered: Jason Rubin

Naughty Dog co-founder Jason Rubin started making games at age 14 and hasn't stopped.

Listen

The Tim Ferris Show: Bill Burr

Bill talks about how he found his way into standup comedy.

Listen

The AIAS Game Maker's Notebook: Neil Druckmann

Naughty Dog's Neil Druckmann and Ted Price discuss trailer reactions, The Last of Us, narrative vs gameplay, and the drive to create something meaningful.

Listen

Ben Greenfield: The Ultimate Coffee Podcast

A deep dive into the subject of coffee.

Listen

Articles

Articles in this issue are based on the topics: machine learning, data science, blogging, and intermittent fasting.

Initializing neural networks

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Parameter optimization in neural networks

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Feature Visualization: How neural networks build up their understanding of images

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I wasn’t getting hired as a Data Scientist. So I sought data on who is

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MS or Startup Job — Which way to go to build a career in Deep Learning?

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Succeeding as a data scientist in small companies/startups

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What I Learned from Writing a Data Science Article Every Week for a Year

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My Self-Created Artificial Intelligence Masters Degree

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Doing Data Science at Twitter

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Interview with The Co-Founder and Researcher at Fast.ai: Dr. Rachel Thomas

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Alternatives to a Degree to Prove Yourself in Deep Learning

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Advice for Better Blog Posts

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What You Need to Know Before Considering a PhD

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The Beginner’s Guide to Intermittent Fasting

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The real reason intermittent fasting works

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Tweets

Below are some of the tweets I've bookmarked over the years that I consider worthy of cataloging. Tweets are in no particular order.

Videos

Videos in this week's issue are based on the topics: deep learning, education, productivity, health, and movie discussion.
















Going forwards, I'll be creating digests like this one and releasing them on a periodic basis. Let me know below if you found this useful. I'd also appreciate any feedback/criticism.