I freelance remotely, making roughly $1200 a month as a programmer because I only work 10 hours maximum each week (limited by my contract). I share the apartment with my mom, and It's a section 8 so our rent contributions are based on the income we make. My contribution towards rent is $400 a month.
Although I make more money than my mom (she's of retirement age and only works 1-2 days a week), while I'm looking for more work I want to figure out how to move out and live more independently on only $1200 a month.
I need to live frugally and want to know what I can cut more easily. I own a used car (already paid in full), and pay my own car insurance, electricity, phone and internet. After all that I have about $400 left each month which can be eaten up by going out or some emergency funds.
More recently I had to pay for my new city parking sticker so that's $100 more in expenses this particular month. I would be satisfied just living in a far off town paying the same $400 a month, I feel my dollars would stretch further since I now get 100% more privacy for the same price.
On top of that this job is a contract job so I need to put money aside to pay my own taxes. This $1200 is basically living on poverty level. Any ideas to make saving work? Is it very possible for people in the US to still save while on poverty?
What kind of workflow do you employ when designing a data-flow or analyzing data?
Let me give a concrete example. For the past year, I have been selling stuff on the interwebs through two payment processors one of them being PayPal.
The selling process was put together with a bunch of SaaS hooking everything together through webhooks and notifications.
Now I need to step it that control and produce a proper flow to handle sign up, subscription and payment.
Before doing that I'm analyzing and trying to conciliate all transactions to make sure the books are OK and nothing went unseen. There lies the problem. I have data coming from different sources such as databases, excel files, CSV exports and some JSON files.
At first, I started dealing with it by having all the data in CSV files and trying to make sense of them using code and running queries within the code.
As I found holes in the data I had to dig up more data from different sources and it became a pain to continue with code. I now imported everything into Postgres and have been "debugging" with SQL.
As I advanced through the process I had to generate a lot of routines to collect and match data. I also have to keep all the data files around and organized which is very hard to do because I'm all over the place trying to find where the problem is.
How do you handle with it? What kind of workflow? Any best practices or recommendations from people who do this for a living?
Too many business scripts rely on cron(8) to run. Classic cron cannot handle task duration, fail (only with email), same-task piling, linting, ...
So what is your favorite open-source, easy to bundle/deploy job scheduler, that is easy to use, has logging capacity, config file linting, and can handle common use-cases : kill if longer than, limit resources, prevent launching when previous one is nor finished, ...
There are a lot of fields I'm interested in, such as machine learning, but I struggle to understand how they work as most resources I come across are full of complex mathematical notation that I never learned how to read in school or University.
How do you learn to read this stuff? I'm frequently stumped by an academic paper or book that I just can't understand due to mathematical notation that I simply cannot read.
I've been thinking for some time now that as productivity keeps growing, not all people will need to work any more. Society will eventually start to resemble an open source project where a few core contributors do the real work (and get to decide the direction), some others help around, and the majority of people just benefit without having to do anything. I'm wondering if any books have been written to explore this concept further?
I want to build an online course on graph algorithms for my university. I've tried to find a solution which would let submit, execute and test student's code (implement an online judge), but have had no success. There are a lot of complex LMS and none of them seem to have this feature as a basic functionality.
Are there any good out-of-box solutions? I'm sure I can build a course using Moodle or another popular LMS with some plugin, but I don't want to spend my time customizing things.
I'm interested both in platforms and self-hosted solutions. Thanks!
Besides classification and regression, and the unsupervised methods for principle components, clustering and frequent item-sets, what tools are there in the ML toolkit and what kinds of problems are amenable to their use?
Are batteries the primary justification for "buy all sell all" over "net metering"?
Are next-gen supercapacitors the solution?
My side project is beginning to attract interest from a few people who would like to hop on board. At this point I am just doing what feels familiar and sensible, but the project manager perspective is new to me. Are there any sort of articles/books/podcasts/etc that could clue me into how to become better at it?
Reading Troy Hunt's password release V2 blog post , I came across the NIST recommendation to prevent users from creating accounts with passwords discovered in data breaches. This got me thinking: would a website admin (ex. small business owner with a custom website) benefit from a service that validates user passwords? The idea is to create a registration iframe with forms for email, password, etc., which would check hashed credentials against a database of data from breaches. Additionally, client-side validation would enforce rules recommended by the NIST's Digital Identity Guidelines , which would relieve admins from implementing their own rules. I'm sure there are additional security features that can be added.
1. Have you seen a need for this type of service, and could you see this being adopted at all?
2. Do you know of a service like this? I've looked, no hits so far.
3. Does the architecture seem sound?
Also, how has it affected your CS career? I feel that transitioning to management would help, as it does not require lengthy periods of concentration, but rather distributed attention for shorter periods.
We have been hosting a Ugandan refugee in our home in Oakland for the past 9 months and he wants to learn how to code.
Where is the best place for him to start from absolute scratch? What resources can we point him to? Who can help?
These days there is a tendency in data analysis to use Jupyter Notebooks. But what happens if you have too many jupyter notebooks? For example, there are more than a hundred.
Actually, you start creating some modules. However, it is less convenient to work with them compared to what was before. It happens that you should code in web interface, somewhere in similar to the notepad++ form or you should change your IDLE.
Personally, I work in Pycharm and so far I couldn't assess remote interpreter or VCS. It is because pickle files or word2vec weighs too much (3gb+) and so I don't want to download/upload them. Also Jupyter is't cool in pycharm.
Do you have better practices in your companies? How to correctly adjust IDLE? Do you know about any possible substitution for the IPython notebook in the world of data analysis?
There are some cool YouTube channel suggestions on https://news.ycombinator.com/item?id=16224165 But I wanted to know which of those are great to progress into advanced level of programming? Which of the channels teach advanced techniques?
I am a full-time Android developer who does most of his programming work in Java. I am a non CS graduate so didn't study Data structure and algorithms course in university so I am not familiar with this subject which is hindering my prospect of getting better programming jobs. There are so many resources out there on this subject that I am unable to decide which one is the best for my case. Could someone please point me out in the right direction. Thanks.
I often find myself "needing" to take a mini-break after just a few minutes of concerted effort while coding. In particular, this often occurs after I've made a tiny breakthrough, prompting me to reward myself by checking Twitter or HN. This bad habit quickly derails any momentum. What are some tips to increase focus stamina and avoid distraction?
I was speaking with a person years my senior awhile back, and sharing information about the Quantopian platform (which allows users to backtest and share trading algorithms); and he asked me "why would anyone share their trading algorithms [if they're making any money]?"
I tried "to help each other improve their performance". Is there a better way to explain to someone who spends their time reading forums with no objective performance comparisons over historical data why people would help each other improve their algorithmic trading algorithms?
I won't go into details to keep this brief, but I'm going to spend a week with this client of mine's kit, and I'm supposed to teach him enough about programming for him to figure out if it's something he might be interested in pursuing.
He's about 20, and still struggling to finish high school, but he's smart (although perhaps a little weird).
I thought about introducing him to touch typing just to get a useful skill out of this regardless of the outcome. Then, I thought that during this week I'd teach him HTML and enough CSS to see what's used for. I'm thinking that if he gets excited about typing code and seeing things happening he'll want to study more and learn more advanced stuff in the future and perhaps even make it his profession (this is what my client hopes will happen).
Now, part of this trip is a 12-hour drive. I thought I could use this time to introduce him to simple programming concepts. For instance, if asked to list all steps involved in starting a car, most people would say:
- turn key - start car
That could turn into an infinite loop, though. A better way would be:
- turn key - start car - if it starts, exit - if it doesn't start, repeat 3 more times - if it still won't start, call a mechanic
Stuff like this—that anyone can understand, that can be explained without looking at a computer, but that it's still useful.
Any idea what I could talk about? Examples, anecdotes, anything.
I'm 17 and I can code at a relatively high level. I'm not really sure what I should be doing. I would like to make some money, but is it more useful to me to contribute to open-source software to add to my portfolio or to find people who will hire me? Even most internships require you to be enrolled as a CS major at a college. I've also tried things like Upwork, but generally people aren't willing to hire a 17-year-old and the pay is very bad. Thanks for any advice!
My GitHub is: https://github.com/meyer9
I'm interested in writing a utility to assist with scheduling un-conferences. Lets take the following situation for an example:
* 4 conference rooms across 4 time slots, for a total of 16 talks.
* 30 proposed talks
* 60 total participants
Each user would be given 4(?)votes, un-ranked. (collection of the votes is a separate topic) Voting is not secret, and we don't need mathematically precise results. The goal is just to minimize conflicts.
The algorithm would have the following data to work with:
* List of talks with the following properties:
I'd like to come up with an algorithm that does the following:
* presenter participant ID * the participant ID for each user that voted for the talk
* fills all time slots with the highest voted topics
* attempts to avoid overlapping votes for any particular given user in a given time slot
* attempt to not schedule a presenter's talk during a talk they are interested in.
* Sugar on top: implement ranked preferences
My question: where do I start to research the algorithms that will be helpful? I know this is a huge project, but I have a year to work on it. I'm also not overly concerned with performance, but would like to keep it from being exponential.
Thank you for any references you can provide!
Was just Googling around for whether Excel (sans VBA scripting of course) is Turing-complete, in order to decide whether telling a layperson that Excel (or spreadsheeting in general) can be considered very much like programming. Came across this 2009 HN thread, "Ask HN: What can't you do in Excel?" from pg:
> One of the startups in the current YC cycle is making a new, more powerful spreadsheet. If there are any Excel power users here, could you please describe anything you'd like to be able to do that you can't currently? Your reward could be to have some very smart programmers working to solve your problem.
What significant advances -- in Excel/spreadsheets, not the Turing-complete thing -- have been made in the 8 years since? What's the YC startup from that cycle that "is making a new, more powerful spreadsheet", and what is it doing today? I remember Grid , but that was from 2012. Any other companies make innovations that would overturn the spreadsheet paradigm, or at least be copied by Excel/OO/GSheets?
A commenter mentioned "Queries", since many spreadsheet users use spreadsheets like a database. I just recently noticed that GSheets has a QUERY function  that uses "principles of Structured Query Language (SQL) to do searches). The function has been around since 2015 (according to Internet Archive ) so perhaps I ignored it because its description then was simply, "Runs a Google Visualization API Query Language query across data."
It appears that "Visualization API Query Language" has a lot of SQL-type features with the immediately obvious exception of joins .
edit: Multiple people said they would like Excel to have online functionality, i.e. like Google Sheets, but being able to accept VBA and any other features of legacy Excel spreadsheets. There's now Excel Online but I haven't used it (still sticking to Office 2011 for Mac if I ever need to use Excel instead of GS). How seamless is the transition from offline, legacy Excel files to online Excel?
I see a lot of people from other industries, say designers or sales people, who can set for themselves actionable and measurable goals such as "Make one illustration a day", "Make a logo a day" or "Sell X units of Y product a day", "Make X ammount of dollars seeling product Z by date X", etc.
How do you, as a developer, set measurable goals for yourself, being it at work or in your side hobbie?
Ask HN: How do IPOs and ICOs help a business raise capital?
IPO: "Initial Public Offering"
ICO: "Initial Coin Offering"
Hey everyone, I'm teaching an undergraduate class in the fall at a local university here in Miami (FIU) and would love your recommendations on what books or articles or frameworks you think the students should read. My goal for the class is to teach them how to identify problems and prototype solutions for those problems. Hopefully, they make some money from them to help pay for books, etc.
In tech circles, it seems that Bayesian statistics is often favored over classical frequentist statistics. In my study of both Bayesian and frequentist statistics, it seems that the results of a Bayesian analysis are generally more intuitive, such as when comparing Bayesian credible intervals to frequentist confidence intervals. It also seems like Bayesian analysis avoids what I think is one of the most serious problems in analysis, the multiple comparisons problem. It's been easy for me to find any number of Bayesian critiques of frequentist stats, but I have rarely seen frequentist defenses against Bayesian stats. This may simply be because I mostly read technology related sites as opposed to more general statistics oriented sites. As such, I would really appreciate hearing some frequentist critiques of Bayesian stats. I feel like the situation can't be as cut and dry as one being better than the other in all things, so I would like to acquire a more balanced perspective by hearing about the other side. Thanks!
So I was reading Richard Stallman's blog on why you should not use google/uber/apple/twitter etc and I understand his reasoning. But what I don't understand is how would one go about building a startup or business that develops and distributes free software only and make good money doing so?
For example, would it be possible to build a free software version of uber/twitter/facebook etc? How would that work?
By removing all restrictions on the software, what is the incentive to not pirate the software? The GPL can be enforced, but that is clearly not practical especially outside the US.
I'm in my late twenties and I'm having a bit of a tough time dealing with my level of programming skill.
Over the past 3 years, I've released a few apps on iOS: not bad, nothing that would amaze anyone here. The code is generally messy and horrible, rife with race conditions and barely holding together in parts. (Biggest: 30k LOC.) While I'm proud of my work — especially design-wise — I feel most of my time was spent on battling stupid bugs. I haven't gained any specialist knowledge — just bloggable API experience. There's nothing I could write a book about.
Meanwhile, when I compulsively dig through one-man frameworks like YapDatabase, Audiobus, or AudioKit, I am left in awe! They're brimming with specialist knowledge. They're incredibly documented and organized. Major features were added over the course of weeks! People have written books about these frameworks, and they were created by my peers — probably alongside other work. Same with one-man apps like Editorial, Ulysses, or GoodNotes.
I am utterly baffled by how knowledgeable and productive these programmers are. If I'm dealing with a new topic, it can take weeks to get a lay of the land, figure out codebase interactions, consider all the edge cases, etc. etc. But the commits for these frameworks show that the devs basically worked through their problems over mere days — to say nothing of getting the overall architecture right from the start. An object cache layer for SQL? Automatic code gen via YAML? MIDI over Wi-Fi? Audio destuttering? Pff, it took me like a month to add copy/paste to my app!
I'm in need of some recalibration. Am I missing something? Is this quality of work the norm, or are these just exceptional programmers? And even if they are, how can I get closer to where they're standing? I don't want to wallow in my mediocrity, but the mountain looks almost insurmountable from here! No matter the financial cost or effort, I want to make amazing things that sustain me financially; but I can't do that if it takes me ten times as long to make a polished product as another dev. How do I get good enough to consistently do work worth writing books about?