danoneata

from functools import singledispatch


class Document:
    pass


class Paragraph(Document):
    def __init__(self, text):
        self.text = text

danoneata

Course info

• Motivation: Deep learning in vision, speech, text, robotics.

• Deep learning courses:

  • Andrew Ng: Deep Learning
  • fast.ai: Practical Deep Learning For Coders
  • Stanford: CS231n Convolutional Neural Networks for Visual Recognition

• Oxford: Machine Learning

danoneata

{-# LANGUAGE TypeOperators #-}
{-# LANGUAGE GeneralizedNewtypeDeriving #-}   
                                                           
import Control.Applicative
import Data.Char
import Data.List (intersperse)
import Data.Monoid hiding (All, Any)
import Data.Foldable hiding (all, any)
import Prelude hiding (all, any)

danoneata

from typing import (
    List,
    TypeVar,
)

# Type aliases
A = TypeVar('A')
Digit = int
Matrix = List[List[A]]
Grid = Matrix[Digit]

danoneata

/**
  * Created by eurus on 28/02/2017.
  */
package components

import collection.immutable.Queue
import ActionType._

sealed trait SignalValue
object `0` extends SignalValue {

danoneata

import logging

from gensim.models.doc2vec import (
    Doc2Vec,
    TaggedDocument,
)

logging.basicConfig(
    format='%(asctime)s : %(threadName)s : %(levelname)s : %(message)s',
    level=logging.DEBUG,

danoneata

def descriptors_to_sufficient_statistics(xx, gmm, **kwargs):
    # yael assumes that the data is in C-contiguous format.
    xx = np.ascontiguousarray(np.atleast_2d(xx))

    N = xx.shape[0]
    K = gmm.k
    D = gmm.d

    # Compute posterior probabilities using yael.
    Q = gmm_predict_proba(xx, gmm)  # NxK

danoneata

class Expr(object):
    def accept(self, visitor):
        method_name = 'visit_{}'.format(self.__class__.__name__.lower())
        visit = getattr(visitor, method_name)
        return visit(self)


class Int(Expr):
    def __init__(self, value):

danoneata

class Expr(object):
    def accept(self, visitor):
        method_name = 'visit_{}'.format(self.__class__.__name__.lower())
        visit = getattr(visitor, method_name)
        return visit(self)


class Int(Expr):
    def __init__(self, value):
        self.value = value

danoneata

import numpy as np


def fvecs_read(filename, c_contiguous=True):
    fv = np.fromfile(filename, dtype=np.float32)
    if fv.size == 0:
        return np.zeros((0, 0))
    dim = fv.view(np.int32)[0]
    assert dim > 0
    fv = fv.reshape(-1, 1 + dim)