add more info to README

README.md

@@ -2,15 +2,76 @@
 
 <h1>La Classy</h1>
 
-~~This library is veeeeeeeery unstable (like my mood swings)~~.
-This library is almost stable.
+Single Layer Perceptron (SLP) library for Deno.
 
-WIP single layer perceptron library for Deno.
+This library is written TypeScript and Rust and it uses FFI.
 
-Supports:
-- Gradient descent (normal, stochastic, minibatch)
-- Optimizer for linear models (Adam)
-- Schedulers for learning rate
+## Why Classy?
+
+- It's fast.
+- It gives you some freedom to experiment with different combinations of loss functions, activation functions, etc.
+- It's easy to use.
+
+## Features
+
+- Optimization Algorithms:
+  - Gradient Descent
+  - Stochastic Average Gradients
+  - Ordinary Least Squares
+- Optimizers for updating weights:
+  - RMSProp
+  - ADAM
+- Schedulers for learning rate:
+  - One-cycle Scheduler
+  - Decay
+- Regularization
+- Activation Functions:
+  - Linear (regression, SVM, etc.)
+  - Sigmoid (logistic regression)
+  - Softmax (multinomial logistic regression)
+  - Tanh (it's just there)
+- Loss Functions:
+  - Mean Squared Error (regression)
+  - Mean Absolute Error (regression)
+  - Cross-Entropy (multinomial classification)
+  - Binary Cross-Entropy / Logistic Loss (binary classification)
+  - Hinge Loss (binary classification, SVM)
+
+## Quick Example
+
+### Regression
+```ts
+import { OLSSolver } from "https://deno.land/x/classylala/mod.ts";
+
+const x = [100, 23, 53, 56, 12, 98, 75];
+const y = x.map((a) => [a * 6 + 13, a * 4 + 2]);
+
+const solver = new OLSSolver();
+
+solver.train(
+  { data: Float64Array.from(x), shape: [x.length, 1] },
+  { data: Float64Array.from(y.flat()), shape: [y.length, 2] },
+  { silent: false, fit_intercept: true }
+);
+
+const res = solver.predict({
+  data: Float64Array.from(x),
+  shape: [x.length, 1],
+});
+for (const pred of res.rows()) {
+  console.log(pred);
+}
+```
+
+There are other examples in [/examples](https://github.com/retraigo/la-classy/tree/main/examples)
+
+## Documentation
+
+[Deno `/x`](https://deno.land/x/classylala/mod.ts)
+
+## Maintainers
+
+Pranev ([retraigo](https://github.com/retraigo))
 
 Check out [deno-ml](https://github.com/retraigo/deno-ml) for examples!
-Discord: [Kuro's ~~Chaos Abyss~~ Graveyard](https://discord.gg/A69vvdK)
+Discord: [Kuro's ~~Chaos Abyss~~ Graveyard](https://discord.gg/A69vvdK)