So I have this application laid out but I am unsure on some aspects of how to go about it.
It's a website for dogs with cancer to supply a raw ketogenic diet for the user. There are other aspects of the website that I have figured out like where to hold state and such.
Where I'm a little confused on how to proceed is on the calculations for the ketogenic page shopping cart. The user can choose 1 fat source from the sources provided, one protein source and one green vegetable source. I want to make this as balanced and complete for the user for their dog- so obviously 1-protein 1 veg and 1 fat source is not balanced and complete. I need to factor in the amount of calories need per weight which I will have an input where the user can enter their dogs weight. I have done some of the math to make it complete and balanced on paper, factoring in amino acids, vitamins and minerals and the omega 6:3 ratio.
What I'm confused about is where am I going to hold all this data per se? It's a lot of data and it's based on many factors such as weight-activity, keto ratio like 1:1 or 2:1 depending what the user selects.
I obviously need a backend and need to build an API, but how would I return to the user the complete and balanced diet when so many other factors play in? Where would I store this other data? In objects? Variables? And then put it on the backend? I would greatly appreciate any help. Thanks in advance.
how are you? First of all, congrats on the great idea, I think it is great.
For starters, I think it's important for you, to lay down what technologies you'll be using.
1- Choose the technologies you are going to use. Will you use the MERN stack? React for front-end, mongo for the database, node.js for back-end with express.js as a framework?
2- Will you be the one providing all the data for the dog's diets? If not, find some website with an API for that data.
3- I am not any kind of expert on JS nor React.js, I'm just following the logic here. But does that data change? or is it always the same? I would advise you to use objects, so you can "play" with them, pass them around the classes (I would advise you to create a react class, where you store all of those objects, make sure you export that class)
4- Just lay everything out and START BUILDING!!! It sounds hella overwhelming to start such a big project, but once you get going some i's will be dotted, you will get a better understanding of what you actually are going to build.
5- Few tips, if you use an API you won't need to store the data, else store it on your database (JSON file, for example, there are great youtube tutorials on how to do so.)
Keeping this in mind, you asked where you'll be storing all that data, if you have an api, you won't store anything, if you don't, JSON is your best shot, it's really easy and intuitive to use and easy to read inside a react component.
I hope this gave you some extra clarification on what you'll need to do, in order to start.
PS: This answer is purely based on my limited React (and web dev) experience, I am no expert, let me know if there's anything else I can help you with.
Related
So, a little bit on my problem.
TL;DR
Can I use machine-learning instead of Elastic Search to find results depending on the user's text input? Is it a good idea?
I am working on a car spare parts project, and we have split the car into 300 parts that we store on the database, with some data for each part (weight, availability, etc).
When the customer inputs the text of his part, we need to be able to classify the part, and map it to one in our database.
The current way it's being done is by people on our team manually mapping the customer text with the parts on our database, we want to automate that process.
We tried using MongoDB text search, but it was often inaccurate since parts have different names in different parts of the country.
So we wanted something that got more accurate results, and improved by the more data we have, we immediately considered TensorFlow, after some research and taking part of Google's Machine Learning Crash Course, I got to that point where it specified:
Models can't learn from string values, so you'll have to perform some feature engineering to convert those values to something numeric
That would be useful in the case we have limited number of features as strings, but we don't know what the user will input as a text.
So, my questions are:
1- Can we use Machine Learning to map text input by the user with some documents on our database?
2- If we can do that, is it a good idea to favor it over other search tools like ElasticSearch?
3- Can ElasticSearch improve its results the more data we have? How?
4- How would you go about this problem?
Note: I'd be doing that in Node.js, and since TensorFlow.js is new, I am inclining to go for other solutions, but if push comes to shove, and the results are much better, I would definitely go there.
TL;DR: Yes and yes.
TS;WM:
This is a perfectly suited problem for machine learning. Especially so, if you have a database of past customer texts that have already been mapped to parts. Ideally, you have hundreds of texts mapped to each part. If that is present, you can design and train a network. And models can learn from string values with some engineering, and it's not that bad.
I'm not sure ElasticSearch would improve much on the network. I don't know much about auto parts trading, but as a wild guess, "the large round thingy that helps change direction" would never be mapped to "steering wheel" by ES but could be learned easily by a network - provided there are at least some examples of people using that text to specify steering wheel.
You can but don't have to necessarily use tensorflow.js for your network. The AI could run on your server as a webservice, and you'd just send over the customer's text to it and it would send back it's recommendations of part SKUs and names.
I am in the process of developing some Use Cases for a mobile mapping/gps app. Users will be able to use this app similar to google maps. I was wondering if anyone had valuable input into some possible use cases.
Here are some I came up with myself:
1) Get Current Location
2) Set Destination Location
3) Create Fastest Route
4) View Alternative Routes
5) Traffic Estimation on Routes
If someone could help me elaborate or comment on my direction that would be helpful!
My first impulse was to flag your question as "too broad", as you basically ask to help you with your requirements analysis. But I give a few hints.
Your 5 use cases don't look bad. But they appear to be just a first rough sketch of the functionality of your app, that needs to be refined. A good model, be it UML or anything else, must be helpful for its reader to gain some insight. Now these 5 use cases could be named by any child who has seen a navigation device once in her life. To be meaningful, questions like the following should be asked and will probably lead to a more detailed use case analysis:
How are destination locations selected? If there is more than one place called Jacksonville, how will the user be informed, and how will she select the right one? Does selecting the location consist of more than one step, say country - city - road - block, to assist the user?
How do map data get into the application?
What kind of alternative routes are considered and how should they be calculated?
How will traffic data get into the application?
Try to put yourself into the developer's position. Which questions will she need to have clarified to build the right application?
So here's my question. Supposing that one is about to create an online web appliation that takes as user input a current location and a location for destination, and displays as a result one of the 5-6 available routes that are stored in a database that is most suitable in terms of distance,and Open Street Map data and Open Layers are used which would be the best way to make this happen?
What I am asking for is what would I need for:
1.Storing the data in database
2.Do the routing calculations. If I would like to change a bit the algorithms for academic reasons and have more control of my final result how would I do that? Do I need any programming language? Any good tutorials?
3.What is the difference between using pgRouting and using any custom solution(like mentioned above)? Doing the all the coding again by myself would be like reinventing the wheel?
4.What would be best for a commercial website, where fast calculations would be needed?
UPDATE: What I need is a way to connect 1.user input(as geometry points) 2.Routing algorithm I have written 3.Road Network and return a result in terms of best way to go to a point
Please see the list of online routers and offline routers for OSM as well as the general wiki page about routing with OSM.
If that still doesn't answer your questions, ask a more specific one.
This is my first time dabbling in NLP so please excuse my ignorance. I'm looking for a method to extract interests/likes/hobbies from users' social profiles. Here is an example where all the interests/likes/hobbies are in bold:
"I consider myself a pretty diverse character... I'm a professional
wrestler, but I'd take a bullet for Wall•E. I train like a one-man genocide machine in the gym, but I cried at
"Armageddon." I'll head bang to AC/DC, and I'm seriously
considering getting a Legend of Zelda tattoo. I'm 420-friendly. I
like to party it up with the frat crowd one night, hang out with
my Burning Man friends the next, play Halo and World of
Warcraft the next, and jam with friends that aren't any younger than
40 the next. My youngest friend is 16, my oldest friend is 66. I'll
sing karaoke at the bars, and I'm my friends' collective
psychiatrist/shoulder."
The profiles are plain text. There are no meta tags or ids associated with any of it, it's just a paragraph of text.
My naiive idea was to take each noun and match it against Freebase to see if it's an activity/artist/movie/book etc. The problem is that although most entities mentioned will be things the user likes, she will also mention things she doesn't like and I have no means of distinguishing the 2.
I have 2 questions:
What sub field of NLP should I be looking at? Some googleable algorithms/techniques/authors would be greatly appreciated.
How hard is this problem?
Thanks!
First, unless using NLP to do this is a particular objective for you, check your problem domain to see if you can avoid it completely.
For instance:
do these profiles have tags (supplied either by the Site or by the
user)?
what does the Site's API make available (assuming that's how you are accessing this data; if you are scraping it, then this doesn't of course apply)? A good example, Facebook. if you read a user's posts, you'll see words like "wrestler", "karaoke", etc. but if you look at what fields are exposed via the Graph API, you'll see that these activities nearly always have an associated FB ID.
I am not a specialist in this field, but I can recommend a couple of resources directed to NLP and which are accessible to the non-specialist or novice. The first is a text processing API. This simple web service uses REST and JSON IO. It is free and seems to have a fairly large rate limit.
This API appears to rely heavily on the excellent Natural Language Tooolkit (NLTK) which is a mature stable library in python, that includes modules directed to the problem in your Question, e.g., Sentiment Analysis, Tagging and Chunk Extraction, etc.
Which particular sub-domain is most relevant to solving the Question in the OP? I don't know, but I suspect there's a module somewhere in the NLTK that does what you need. Finding that module is hopefully just a matter of skimming the API Documentation (which is organized by module); reading the Getting Started section which contains an excellent survey of NLTK's modules as well as demos for all of each of them.
I am very new to GIS development, and to be be frank I have no background about it at all. I searched the web but the tutorials I found seemed to assume the reader has some background information.
the thing is that I am confused about what to read or learn, there seems to be lots of technologies, and I feel lost since some speak about openlayers, geoserver, mapserver, google maps, and open street maps.
So here is what I am supposed to develop, and I hove you could give me an advice about which technology to use, and where should I start reading - given that I know almost nothing -.
Case 1: a closed system for about 20 users only, who can specify locations on the map, and the web application will store the latitude and longitude of the locations and show the markers. I wanted to use google maps api, but I cancelled that since there license requires you to purchase the service if the system is a closed one. so what technology should I use in such case? I need a free option, also I will be only using web server, so if the solution includes using my own geoserver, or something like that I won't be able to do it.
Case 2: I am supposed to display the roads and routes between two given points, and probably add some notes on the map. For this I case I can use my own map server/geo server, but again I want your suggestions.
of course the solution need to be open source
finally, I hope you could tell me what to start reading first,
Start by looking over at https://gis.stackexchange.com/, starting with the tags [web-mapping] and
Some topics in particluar you may want to look at are:
https://gis.stackexchange.com/questions/8113/steps-to-start-web-mapping
https://gis.stackexchange.com/questions/8238/where-how-to-learn-about-getting-started-with-web-gis
https://gis.stackexchange.com/questions/13868/looking-for-a-developer-friendly-web-gis
As for skills and tuorials, look at:
https://gis.stackexchange.com/questions/17227/free-gis-workshops-tutorials-and-applied-learning-material
https://gis.stackexchange.com/questions/913/web-gis-development-skill-sets