Best debugging books according to redditors
We found 21 Reddit comments discussing the best debugging books. We ranked the 6 resulting products by number of redditors who mentioned them. Here are the top 20.
We found 21 Reddit comments discussing the best debugging books. We ranked the 6 resulting products by number of redditors who mentioned them. Here are the top 20.
Books:
"Doing Bayesian Data Analysis" by Kruschke. The instruction is really clear and there are code examples, and a lot of the mainstays of NHST are given a Bayesian analogue, so that should have some relevance to you.
"Bayesian Data Analysis" by Gelman. This one is more rigorous (notice the obvious lack of puppies on the cover) but also very good.
Free stuff:
"Think Bayes" by our own resident Bayesian apostle, Allen Downey. This book introduces Bayesian stats from a computational perspective, meaning it lays out problems and solves them by writing Python code. Very easy to follow, free, and just a great resource.
Lecture: "Bayesian Statistics Made (As) Simple (As Possible)" again by Prof. Downey. He's a great teacher.
I've posted this before but I'll repost it here:
Now in terms of the question that you ask in the title - this is what I recommend:
Job Interview Prep
Junior Software Engineer Reading List
Read This First
Fundementals
Understanding Professional Software Environments
Mentality
History
Mid Level Software Engineer Reading List
Read This First
Fundementals
Software Design
Software Engineering Skill Sets
Databases
User Experience
Mentality
History
Specialist Skills
In spite of the fact that many of these won't apply to your specific job I still recommend reading them for the insight, they'll give you into programming language and technology design.
This is a really good book on Bayesian statistics, but Kruschke is coming out with a new edition in about two months with completely different code. It's going to use JAGS and STAN instead of BUGS.
Tfw I'm the most knowledgeable person about statistics I know and I have read 0 of these books. Time to get reading! Although I still want to go with Doing Bayesian Data Analysis: A Tutorial with R and BUGS over Gelman et al because I want to do all the work in R. The book itself has 51 reviews on Amazon, 44 of which are 5 stars, for a mean of 4.8. That seems very good.
Saved this thead for future reference. :)
Learned BASIC from math textbooks, 3-2-1 Contact! magazines, which actually printed an editor chosen submission of a game every month which is awesome, and the Chip Mitchell book series, which was kind of like Encyclopedia Brown except that the case answers were sometimes code debugging puzzles. The funny thing was, I didn't actually start using QBasic until a few years later, but I remembered so much from these that I was able to write up code consisting of PRINT, INPUT and IF statements purely from memory.
If you're looking for a story, here's a good classic non-fiction one:
The Soul of a New Machine by Tracy Kidder
And a fictional one:
The Bug by Ellen Ullman
This is my first time reading this page and I am quite the amateur programmer.
I am an Assistant Professor in Criminal Justice; however, my passion is quantitative methodology and understanding big data.
I had a great opportunity to spend a summer learning Bayesian at ICPSR, but to be honest some of the concepts were hard to grasp. So, I have spent the greater part of the past year learning more about maximum likelihood estimations and Bayesian modeling.
I am currently reading The BUGS Book and [Doing Bayesian Analysis] (https://www.amazon.com/Doing-Bayesian-Data-Analysis-Tutorial/dp/0123814855/ref=sr_1_fkmr1_3?s=books&ie=UTF8&qid=1519347052&sr=1-3-fkmr1&keywords=bayesian+anaylsis+bugs).
I regularly teach linear modeling at both the undergraduate and graduate level. Lately, however, I have become interested in other techniques of prediction such as nearest neighbor analysis. About a month ago, I successfully created a model predicting plant specifications with the help of [Machine Learning with R] (https://www.amazon.com/Machine-Learning-techniques-predictive-modeling/dp/1784393908/ref=sr_1_2_sspa?s=books&ie=UTF8&qid=1519347125&sr=1-2-spons&keywords=machine+learning+in+R&psc=1). Of course, this is probably elementary for many of you here but I still found the process easy to understand and now I'm planning to learn about decision trees and Naive Bayes analysis.
If you work in IT then The Bug by Ellen Ullman is the ultimate in depressing novels. Oh look, this new edition has a computer mouse skull on the cover. Cute! :(
I have a lot of experience in off-road, light weight vehicles. 500cc would be OK for a single seater - a Mini Buggy, not a rail http://i24.photobucket.com/albums/c14/theo44/Bandit/Picture0022.jpg
If you want to go "junkyard car" route, strip a VW Beetle (standard, NOT a super).
To see what can be done (street use) go here:
http://volksrods.com/forum/
If you are thinking car based off-road, you MUST read this before buying ANYTHING: http://www.amazon.com/Baja-Bugs-Buggies-VW-based-off-road/dp/0895861860/ref=sr_1_1?s=books&ie=UTF8&qid=1426456596&sr=1-1&keywords=baja+bugs+and+buggies
If you liked Gone Girl I'll bet you'll like Apple Tree Yard. It's a fast paced well written thriller, much more believable than Gone Girl (which I liked too!)
Keto Meal Prep for Beginners 2019
https://www.amazon.co.uk/Keto-Meal-Prep-Beginners-2019/dp/1078082456/ref=sr_1_2?keywords=keto+meal+prep+beginners+2019&qid=1565741114&s=gateway&sr=8-2
​
Keto Slow Cooker & one-pot meals
https://www.amazon.co.uk/Keto-Slow-Cooker-One-Pot-Meals/dp/1592337805/ref=sr_1_2?keywords=keto+slow+cooker+one+pot&link_code=qs&qid=1565741084&s=gateway&sourceid=Mozilla-search&sr=8-2
have been great for me. Easy, flavourful, full breakdown of macros, loving them
Get this book . Some of it is a bit outdated, but for simple Baja's, it's still the best.
Otherwise, check out the offroad forum on http://shoptalkforums.com . There's plenty of information there, and the people are all really helpful.
Came he to say the exact same. I did a lot of research back in the day and settled on a 64' but iirc the best options were around the 1960 - 1968 but I couldn't tell you the reasons. I spent a lot of time on the samba (as the rest) but I also pretty much memorized the book Baja Bugs and Buggies. https://www.amazon.com/Baja-Bugs-Buggies-VW-based-off-road/dp/0895861860
I wanted to build a baja bug with my dad for my first car, but they're just too damn slow to be a decent daily. He had this book that explained pretty much everything. It's probably cheaper than building a hot rod, since this will basically be a beater and all you have to do initially is adjust the ride height, cut down the fenders a bit, and get some off road tires. Then just go crazy from there.
I was referred to this book:
http://www.amazon.com/Doing-Bayesian-Data-Analysis-Tutorial/dp/0123814855/ref=pd_bxgy_b_img_c
Hey. We can't approve this type of question. You could take it over to /r/statistics maybe.
A couple books I've looked at are Applied Bayesian Statistics and Doing Bayesian Data Analysis. Both are written at a pretty low level. The former kind of falls apart after the first few chapters, but the latter is pretty well respected (my university library had both online for free). Both cover the basics upfront but in different levels of detail. Some of the notations and derivations may be uncomfortable for you in some books (not seeing that you have taken a formal probability course and the types of distributions and procedures you use in Bayes aren't covered in intro-stats... beta, inverse gamma, MLE derivation...) so I'd try to look more at example heavy references. Be sure to specify whether you are looking for books or online references when you re-ask your question.