Wolfram Alpha Android app review

I have been a fan of Wolfram for a while. The impresario is Stephen Wolfram a physicist who turned business bloke to sell and develop his maths software. Maths software is not all that hard to come across on the web. A lot of it is free - from Sage for general maths to R for statistical work the field is well populated. Mathematica though seems to be in a different league. I am not working in maths, but did a degree in it while in college. I think I have an idea of what I am talking about and this has pushed me to want a copy of Mathematica. I have not taken the plunge yet as the full version for home use is €175. This is a bit beyond my budget at the moment, but soon I reckon I will take the plunge.
Their computation engine is called Wolfram Alpha. Although a bit clunky (return values of the I did not understand that input sort, spring to mind) the idea behind it is solid. There are a lot of sources of data on the web, but standard queries just pass the data back to you. If you are clever and know some R, you can process this and produce a nice graph (if you are using excel for this, you are trying to open a beer with a cheese grater - it might happen for you, but it is not going to be any fun :)). If you are not so experienced, then you primarily use the web to grab other peoples analyses and read them. Bit one way. So much for interactivity. Alpha tries to change all that. It knows about a whole lot of data sources and how to compare them. It will allow you to input 2 stocks and it will compare them - nothing new there. But you can also compare things like chemicals. Enter 2 chemicals and you will get a bunch of tables showing their properties relative to one another.
The Wolfram Alpha app is basically a view into their on line offering from your phone. The app does not add much over www.wolframalpha.com other than a nice to use keyboard which is savvy to things like Greek letters and mathematical symbols.
This is the only app I have bought - it was just a dollar. I don't use it very often, but still think it was worth it. I was reading a maths book recently and was able to look up stuff like pi (as many digits as liked) from the comfort of my armchair).
Despite the misunderstandings I reckon this is a clever app and is handy for the armchair in all of us. It makes me wonder what I am missing in science.
Overall app rating: 8/10
I know the rating is supposed to be for the app, but with an app that is as lightweight as this one is (basically a fancy keyboard and a licence) the back end cannot be ignored.
Will it be staying on my phone - of course, I did buy it afterall. Until I get a full copy of Mathematica, this will just have to do :)

Comments

Post a Comment

Popular posts from this blog

Building a choropleth map for Irish agricultural data

I wanted to create a choropleth map  using Irish data. The Irish Government has made a large quantity of data available at data.gov.ie. The set I chose was for Bovine TB across Ireland over a number of years. You can get geojson for a variety of countries and Ireland's county boundaries are available. All I had to do was get the data labels to match. In the data some counties are split into 2 parts. I merged and summed these data points to get the choropleth to work with normal county boundaries. You can see the results here . A link to the github is included at the top of the notebook.
Read more

Early Stopping with Keras

Steps to train a model There are a number of things you have to do when working on a Machine Learning problem. Import your data and transform it as appropriate Define  your model using something like Keras - this includes your chosen hyperparameter values Run the training phase Evaluate the model If at the end of this process the evaluation shows that your model is not sufficient for your needs you will need to make some changes and rerun the training.  Ideally you should have a way to spot that training is not going as you want and stop it. This is one of the uses of early stopping. The other is if your model has reached a sufficient quality standard for you to use and further improvements have slowed, stopped altogether or an unnecessary.  Early Stopping Keras provides a way of doing this using the EarlyStopping callback . There are a range of callbacks in Keras and you can define your own. Details are here . The EarlyStopping callback works by choosing a metric
Read more

AutoCompleteTextView backed with data from SQLite in Android

Image
This is a handy piece of code. As your database gets bigger you can allow the user to pick the correct value by typing. If the db gets very big, you can always increase the threshold, so that the query does not run until there will be a suitably sized resultset returned. Running it at a threshold of 1 is fine for very small resultsets.  Here is the code you need to back your AutoCompleteTextView with a cursor adapter. @Override protected void onResume() { super.onResume(); text = (AutoCompleteTextView) findViewById(R.id.autoCompleteTextView1); final AdapterHelper h = new AdapterHelper(this); Cursor c = h.getAllResults(); startManagingCursor(c); String[] from = new String[] { "val" }; int[] to = new int[] { android.R.id.text1 }; CursorAdapter adapter = new MyCursorAdapter(this, android.R.layout.simple_dropdown_item_1line, c, from, to); adapter.setFilterQueryProvider(new FilterQueryProvider() { public Cursor runQuery(Cha
Read more