this week: structure code with types: tuples, records, arrays.

1. USER-DEFINED TYPES

primary use of types: document your code

• use type type_identifier = some_type to define a new type (type_identifier is synonym/abbrevation of some_type)
• type_identifier must start with lowercase letter
• already known types: int, bool, string, char ...
• use : to add …

this week: discuss how to handle events in user-interface — MVC, functional reactive programming.

Lecture 4.1 - Imperative Event Handling: The Observer Pattern

Traditional way of handling events: observer Pattern (MVC). Used when views need to react to change in a model.

MVC: model-view-controller for user interface

• Views can announce themselves …

This week: scala for imperative programming.

Lecture 3.1 - Functions and State

So far: pure functional programming
→ side-effect free: therefore time doesn't matter.
Any rewriting that terminates lead to the same solution. (Churcher-Rosser Th)

Now: mutable states

Stateful objects: objects can have state that change over time. (state is influenced …

1. BASIC DATA TYPES: int, bool

Rich type system and polymorphism in ocaml. Types are infered not declared.

Basic types: int, bool, float, string, char, ...

int

value: $-2^{62}$ ~ $2^{62}-1$ on 64-bit machines.
ops: +, -, *, /, mod (reminder: / is integer division)

# 3+2*4-1;; 
- : int = 10 
# 5/2;; 
- : int …

Lecture 2.1 - Structural Induction on Trees (optional)

Generalize the structural induction on list to general structures like trees.

To prove a property P(t) for all trees t:
* show for any leave l, P(l) holds
* for each internal node t with subtrees s1...sn, show P(s1)&...&P …

上次捣鼓pelican博客系统还是在2012年, 那时farseerfc学长就提供了无私的帮助, 当时非常兴奋写了这么一篇简单的教程.

这两天捣鼓了好久 终于把博客升 …

ref: http://rnduja.github.io/2015/10/26/deep_learning_with_torch_step_7_optim/
doc: https://github.com/torch/optim/blob/master/doc/intro.md

Before we implement the gd update step by defining a gradientUpdate function and calling it in a loop.

function gradientUpdate(model, x, y, criterion, learningRate) 
    local pred = model:forward(x …

ref: http://rnduja.github.io/2015/10/07/deep_learning_with_torch_step_4_nngraph/
doc: https://github.com/torch/nngraph/

The aim of this library is to provide users of nn package with tools to easily create complicated architectures.

luarocks install nngraph

optionally can install graphvis for graph visualization.

From previous posts, to build networks …

ref: http://rnduja.github.io/2015/10/05/deep_learning_with_torch_step_3_nn_criterions/
doc: https://github.com/torch/nn/blob/master/doc/criterion.md

Criterion: abstract class, given input and target(true label), a Criterion can compute the gradient according to a certain loss function.

Criterion class

important methods:

• forward(input, target): compute the …

doc: https://github.com/torch/nn/blob/master/doc/containers.md
ref: http://rnduja.github.io/2015/10/04/deep_learning_with_torch_step_2_nn_containers/

Container, similarly to Module, is the abstract class defining the base methods inherited from concrete containers. Container contains modules (layers).

Container class

important methods:

• add(module)
• get(index): get module …