[OCaml MOOC] week1: BASIC TYPES, DEFINITIONS AND FUNCTIONS

Sun, 23 Oct 2016 Category notes OCaml Series Part 2 of «Introduction to Functional Programming in OCaml»

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 …

[Scala MOOC II] Lec2: Lazy Evaluation

Sat, 22 Oct 2016 Category notes scala Series Part 2 of «Functional Program Design in Scala»

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 …

pelican3建立github博客&主题配置

Wed, 12 Oct 2016 Category soft pelican

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 …

[learning torch] 6. optim (optimization tools)

Mon, 10 Oct 2016 Category notes torch Series Part 6 of «torch学习笔记»

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 …

[learning torch] 5. nngraph (another way to construct nn)

Sat, 08 Oct 2016 Category notes torch Series Part 5 of «torch学习笔记»

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 …

[learning torch] 4. Criterion (loss function)

Sat, 08 Oct 2016 Category notes torch Series Part 4 of «torch学习笔记»

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 …

[learning torch] 3. Container (models)

Fri, 07 Oct 2016 Category notes torch Series Part 3 of «torch学习笔记»

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).