I told her, “mom, the day I become good at math, pigs will fly.” I think pigs just flew.
Solve all type of trigonometric (sin, cos, tan, sec, scs, cot) expressions, equations, inequalities. Solve integral problems - definite, indefinite integrals.
Solve your probability, combination, permutation problems. Statistics - find median, mean (arithmetic, geometric, quadratic), mode, dispersion, mormal distributions, t-Distribution.
If you know a little bit about neural networks (if not, you can read this quick intro I wrote) then I can tell you straight away that the neural network I constructed for this task is A Sequence to Permutation Recurrent Neural Network With Long-Short-Term Memory and Attention. Then, if we know what the structure of the equation is, then we can reduce our problem to finding the correct permutation of the numbers in the input question.
Now, Recurrent Neural Network (RNN) refer to a general architecture in which the network contains some sort of feedback loop.
Now imagine that one day you want to interact with your automatic tutor not only by equations, but also using your natural language. Before we go into the details, let’s think about how we would approach this challenge in general.
Step (1) - when facing a textual math problem, make sure the problem is written in a language that we can read.
You can step by step solve your algebra problems online - equations, inequalities, radicals, plot graphs, solve polynomial problems.
If your math homework includes equations, inequalities, functions, polynomials, matrices this is the right trial account. Include everything above plus finding limits (lim), sums, matrices.
In the next sections, we will see how we perform steps (1)-(2) using existing tools, and how we build a neural network that achieves steps (3)-(4).
First, I did something called Tokenization, where I replaced the numbers in the question with variable names, separated the questions into words and removed punctuation. Then, I did something called Embedding, which means that I “translated” the words into vectors in high dimensional space, in a way that preserves their semantic and syntactic relationships.