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Being honest with yourself is great. Not being able to build anything profitable is much better than tricking yourself into believing you make "profitable" algos on backtest, only to see them all fail in real life.
DO NOT trade forex. FX is super hard to trade: poor data, fragmented markets, most efficient asset class. Finding alpha in FX is 10x harder than in equities/commodities spot/futures.
Unless you are super comfortable with basic stuff DO NOT go to ML, especially deep learning. Simple stuff like momentum, mean-reversion first, then interpretable models, then ensembles of models, then DL. Otherwise you will never learn, nor make any progress at all.
This book is the bible: https://www.amazon.com/Elements-Statistical-Learning-Prediction-Statistics/dp/0387848576/ Read it 100x times and code as much examples yourself as possible.
Networking is networking. There's no difference who does it.
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Regardless, this is a timeless book: https://www.amazon.com/TCP-Illustrated-Protocols-Addison-Wesley-Professional/dp/0321336313
Some books are excellent permanent references.
TCP/IP Illustrated, Volume 1: The Protocols (2nd Edition)
End-to-End QoS Network Design: Quality of Service for Rich-Media & Cloud Networks (2nd Edition)
Other books, as you point out are useful, but perhaps only for shorter periods of time...
Check out the following books:
TCP/IP Illustrated, Volume 1: The Protocols: The Protocols v. 1 (Addison-Wesley Professional Computing) https://www.amazon.co.uk/dp/0321336313/ref=cm_sw_r_cp_api_i_HsfhDb3TC15DK
By Gary A. Donahue Network Warrior (2nd Edition) https://www.amazon.co.uk/dp/B00NBJPIV8/ref=cm_sw_r_cp_api_i_ltfhDbJCDDXG7
Amazon has a 3 book kindle edition for free right now (you can use an app on mobile or your PC as well). I "purchased" it but haven't looked through it yet.
https://www.amazon.com/Python-Manuscripts-Programming-Beginners-Intermediates-ebook/dp/B07CQPHC1N/
Today I stumbled upon a free Kindle Python book set from Amazon here. Maybe it might interest you?
Ports don't mean you have a trojan, it's just an arbitrary identifier to tie a process to an identifier for TCP connections.
Some of them are well known or reserved https://en.wikipedia.org/wiki/List_of_TCP_and_UDP_port_numbers
If you'd like to understand more, this is a great resource: https://www.amazon.com/TCP-Illustrated-Protocols-Addison-Wesley-Professional/dp/0321336313/ref=sr_1_2?dchild=1&keywords=tcp+ip&qid=1603390959&sr=8-2
+1 for CCNA materials. At least the previous CCNA. I'm guessing the new CCNA materials still have all the basics. I did my CCNA 8 or so years into running a network and I learned a lot of the basics I missed or had forgotten.
I think the things to start with are the basics of TCP/IP, what happens when a switch forwards a layer 2 packet, what happens when a switch or router forwards a layer 3 packet & the basics of how spanning tree operates. Memorizing the whole OSI model is a waste of time but knowing what problems/technologies are layer 2 and what are layer 3 is important.
This is a good book to read: https://www.amazon.com/TCP-Illustrated-Protocols-Addison-Wesley-Professional/dp/0321336313/ref=sr_1_1?dchild=1&keywords=tcp%2Fip&qid=1595705789&s=books&sr=1-1
You don't need to read the exact book if you're not into that kind of learning but you can find the online equivalent.
Buy this book.
Yes, it's from 1994.
Yes, you should buy it used.
TCP/IP Illustrated, Vol. 1: The Protocols @ $15
If you have the money oozing out of your pockets, the updated version is here:
TCP/IP Illustrated, Volume 1: The Protocols 2nd Edition @ 2011 for $65 in hard cover.
IPv4 hasn't changed all that terribly much since 1994. The original print is still a valid source of knowledge.
But the updated edition is a nice improvement.
If you're worried about not doing projects and participating in Kaggle competitions, why not do those things? They're pretty low risk and high reward. If you're feeling shaky on the theory, read papers and reference textbooks, take notes, and implement things that interest you. For deep learning stuff there are some good resources here: https://github.com/ChristosChristofidis/awesome-deep-learning. For more traditional methods you can't go wrong with Chris Bishop's book (try googling it for a cheaper alternative to Amazon ;): https://www.amazon.com/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738. Side projects can really help here, and the key is to use references, but don't just copy-paste. Think of something you'd like to apply machine learning to with a reasonable scope. Search google scholar/arxiv for papers that do this or something similar, read them, and learn the techniques. For reading research papers in an area where you're not extremely knowledgeable, use the references in the text or google things you don't know and make sure you understand so you could teach someone else. If you're interested in the topic and exhausted the references, go up the tree and use google scholar to find papers that list the one you're reading as a reference - you usually find interesting applications or improvements on the technique. You can also often find open source training data in the appendices of papers. Kaggle also has a ton of datasets, including obviously the ones they provide for competitions.
I think with networking the protocols is more important than the hardware. Master TCP/IP to be specific and branch out from there. I'm learning Linux right now so I'm going to throw that in there. I'm running GNS3 on it via KVM.
I remember this book as highly recommended but it seems pretty old and don't know if it's still reference material. Has anyone read it recently? TCP/IP Illustrated, Volume 1: The Protocols
If it's obsolete, is there another book you can recommend to the OP and me?
I haven't, but my experience is that learning how TCP/IP works is sufficient. Once a person know's how modern networks function it's easy to reason ones way thought problems/tasks, regardless of new hardware. Network hardware engineers only increase the bits per second, the number of ports, etc... but under the hood it's still TCP/IP - just on a faster ASIC.
TCP/IP Illustrated vol 1 is the best book I've found on the subject. Vol 2 & 3 are great too. Vol 2 is the C implementation of the TCP/IP stack in a BSD variant (FreeBSD, I think). Vol 3 is supplemental information on common protocols (like HTTP) built on top of TCP/IP.
Chapter 6 is dedicated to the discussion of DHCP.
USA, I'd say do the Designing data intensive applications but that's the long route.... try this book: https://www.amazon.com/System-Design-Interview-insiders-Second/dp/B08CMF2CQF/ref=sr_1_1_sspa?keywords=system+design&qid=1660526006&sprefix=system+des%2Caps%2C128&sr=8-1-spons&psc=1
yeeeuuuuuuuuuup. Basically you're going to need to do the research equivalent of DFS.
Whenever you hit a term you don't understand, keep digging at it till it makes sense. Then you have that concept unlocked forever. Also some book like System Design Interview are decent for being exposed to an extremely high level + simplified look of systems
You'll pick it with time for sure though as long as you try to learn
First. Good luck on your interview, hope it goes well.
I've been interviewing for months, and the types of question vary so incredibly wildly that you really can't prepare easily. Unless you know in advance that they use a leetcode type test, or are at least given a topic in advance you will most likely be surprised.
I've seen a mix of both good and bad questions ranging from "Parse a JSON string and aggregate the properties", to "Design a key-value store", to "build a hashtable based tree from scratch".
Don't stress to much, Focus more on the areas you can more easily prepare for. This is a great book: https://www.amazon.com/System-Design-Interview-insiders-Second/dp/B08CMF2CQF
>You can’t really propagate the uncertainty easily, also regression and ML models are mostly discriminative and so they are modeling Y|X, that means it is inherently conditional on the input data features X and thus the uncertainty in X does not need to be propagated even from a statistical point of view. Its already by definition conditional on assuming that X takes that value.
This comment is exactly right. u/rednirgskizzif, if you don't have the book yet, check out the book "Elements of Statistical Learning" section 2.4, equations 2.9 - 2.13. There they show the fundamental approach to minimizing the the *squared error loss* E(Y-F(X))^2 to find the best fit regression function f(x) = E(Y|X=x), which is *not* a chi2 which takes into account measurement uncertainty shown in equation 1 here!)
It's a bit more simple in some ways, but I agree u/rednirgskizzif that our training in physics leads us to care very much about uncertainties in models in a way that in data science/business world there aren't as many applications.
System design (read: distributed systems design) is a fundamental aspect of most senior software engineering interviews. I just went through it myself.
Your husband should check out this book.
https://www.amazon.com/dp/B08CMF2CQF is pretty good. It goes over a good way to answer system design questions and covers some of the common questions that are asked.
A reference book if you want to go deep is the TCP/IP Illustrated (vols 1-3) by Richard Stevens (https://www.amazon.com/TCP-Illustrated-Protocols-Addison-Wesley-Professional/dp/0321336313/ref=mp_s_a_1_1?crid=17A3RYJTLOQ23&keywords=tcp+ip+illustrated&qid=1643930821&sprefix=tcp+ip%2Caps%2C320&sr=8-1). He wrote other books in this field too, all very well regarded.
And the Kozierok book TCP/IP Guide (https://www.amazon.com/TCP-Guide-Comprehensive-Illustrated-Protocols/dp/159327047X/ref=mp_s_a_1_2?crid=17A3RYJTLOQ23&keywords=tcp+ip+illustrated&qid=1643930864&sprefix=tcp+ip%2Caps%2C320&sr=8-2). This one I don't know, but I always read good things about it.
Just a hunch going on the question is maybe if a high level of reads to talk about caching data with redis? Covers the how often does this data need to be invalidated or if a large data size, how do you handle that in memory? Could you break down the db to be read and write connections with multiple slave connections for many reads.
I found this book pretty good as it walks through a number of example designs with the breakdown of scalability in mind https://www.amazon.ca/System-Design-Interview-insiders-Second/dp/B08CMF2CQF
That's how I see it: if it's used for prediction it is machine learning, even if it's a simple linear regression, or GLM.
Some people like to call it statistical learning (this book, great read)
System Design Interview – An Insider's Guide by Alex Xu is a good one.
I think this is a great intro to system design for a much more reasonable price. Plus it comes with an invite to a Discord community where people ask questions and help each other out.
This isn't DDIA, but if DDIA is too intimidating for you then Alex's book is a nice start.
https://www.amazon.com/System-Design-Interview-insiders-Second/dp/B08CMF2CQF/ref=asc_df_B08CMF2CQF/ is ok for learning the kind of system design stuff you'd need for an interview.
When they said a specific db did they mean relational db Vs nosql, or something about a specific piece of dB software?
I have read sections of this book and it’s a pretty good overview of the kinds of questions you might be asked and the kind of answers you should give: System Design Interview – An insider's guide, Second Edition https://www.amazon.com/dp/B08CMF2CQF/ref=cm_sw_r_cp_api_glt_fabc_FA1Q8NMYREK027DS5S6Z
The particulars of the exact questions aren’t super important imo. Try to demonstrate that you know the sorts of high level things to think about and are comfortable with making thoughtful trade offs.
Les salaires des devs vont encore augmenter au cours des 5 prochaines années.
Les boites FR n'arriveront pas à rivaliser avec les boites US qui ont prévu d'investir en Europe et particulièrement en France, mais elles seront quand même obligées de faire de gros effort pour essayer de suivre (cadre de travail, bon manager, Full TT ou à la carte).
Regarder avec le recul de l'international permet d'avoir une meilleure vision.
L'impact des Gafam + Startups US + boites Defi et Cryptos (qui ont littéralement des montagnes de cash) va fortement venir grossir les salaires et c'est tant mieux.
Pour les devs qui auront bossé leur anglais et préparés leurs entretiens (avec ce genre de bouquins) il y aura de sacré opportunités à saisir.
Pour les gens qui s'intéressent au métier de dev : il y a des flopées de formations, certaines ne font que 6 mois et vous permettent déjà d'arriver a beaucoup de choses et à trouver des salaires vraiment correct pour des juniors. Aimer résoudre des problèmes, aimer apprendre et savoir chercher sont de bonnes qualités.
Enfin si vous pensez être sous payé (on pense rarement être surpayé non ?) créez vous le maximum de réseau (et pas juste avec d'autres devs), non seulement cela pourra vous ouvrir les yeux, mais cela pourrait aussi vous ouvrir des portes.
https://www.algoexpert.io/systems/product
https://www.amazon.com/System-Design-Interview-insiders-Second/dp/B08CMF2CQF/ref=nodl_
These are the resources I used to prep for my systems design questions. Before reading the solutions to the included systems design challenges, make sure you try it yourself first and then compare your solution to what is in the book/course. I found that this was super useful for figuring out where my designs needed to be improved.
I would also strongly recommend spending some time practicing drawing diagrams with whatever tool you will be using for the interview.
It's [TCP/IP Illustrated](https://www.amazon.com/TCP-Illustrated-Protocols-Addison-Wesley-Professional/dp/0321336313/ref=sr_1_1?dchild=1&keywords=tcp%2Fip+illustrated&qid=1633547401&sr=8-1). Volume 1 focuses on the protocols in question, which is still pretty relevant today, but it's very nuts-and-bolts. If you're looking to brush up on your IT administration, I'd say this is probably a good book to read after you're already comfortable with the basic concepts. If you want to really grok the network protocols in question, this would also be a good book to read. Other than that, there are probably better introductory texts (though I don't have a recommendation off the top of my head).
The other two volumes focus on implementation and protocols on top of TCP respectively, and both are pretty outdated by this point. I really only have them because I used to work for a company that makes network diagnostic tools, you definitely don't need them.