View Libre-ass.txt
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McEwan defines the "meaning pieces" of reading as language, knowledge, and cognitive strategies. | |
She describes the facets of oral language as "(a) the meanings of words (lexicon). (b) how words are put together in utterances to convey a message (semantics and syntax), and (c) how discourse, or conversational interactions of various kinds, is carried out" (2002, p. 88). Consider how much of the code most children have absorbed by the time they enter school. They hear and understand the meaning of thousands of words, although many of them on a superficial level. They use many of those words in appropriate contexts (and, sometimes, in not so appropriate contexts). They speak in increasingly complex phrases and sentences, at first to express their needs and feelings and gradually to interact with adults and their peers. | |
Capute, Shapiro, and Palmer (1880), in their Clinica/ Linguistio and Auditory Milestone Scale, include these benchmarks for a 3-year-old: uses pronouns discriminately, uses plurals, forms 3-word s |
View arduino_floodfill.cpp
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// | |
// Flood fill algorithm implementation for Arduino | |
// Created by Lakshith on 8/7/22. | |
// | |
struct Coord { | |
int x; | |
int y; | |
}; |
View bitcoin-RNN.py
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import torch | |
import torch.nn as nn | |
from torch.utils.data import Dataset | |
import pandas as pd | |
import numpy as np | |
import torch.optim as optim | |
import matplotlib.pyplot as plt | |
from sklearn.preprocessing import StandardScaler | |
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') |
View IOT.ino
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#include <FirebaseESP8266.h> | |
#include <ESP8266WiFi.h> | |
#include <Wire.h> | |
#include <BH1750FVI.h> | |
#include "DHT.h" | |
#define DHTPIN D1 | |
#define SOIL_DIGITAL_PIN D0 | |
#define SOIL_ANALOG_PIN A0 |
View GAN.py
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import torch | |
import torchvision | |
from torch import nn | |
from torch import optim | |
import pandas as pd | |
import numpy as np | |
from torch.utils.data import Dataset | |
from sklearn.preprocessing import maxabs_scale | |
from torch.utils.tensorboard import SummaryWriter |
View hashcode-2022.cpp
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#include <bits/stdc++.h> | |
using namespace std; | |
int C,P; | |
struct projectStruct{ | |
string name; | |
int days; |
View siriya.cpp
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/** | |
* @author Lakshith Nishshanke | |
* @brief | |
* @version 0.1 | |
* @date 2021-10-23 | |
* | |
* @copyright Copyright (c) 2021 | |
* | |
* Used a greedy approach. Sorted time frames first by their starting time,second by their endind time. | |
* And then greedily checked if it is possible to reserve dates in the sorted order. |
View quarantine.cpp
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#include <bits/stdc++.h> | |
using namespace std; | |
#define int long long | |
struct Flight | |
{ | |
int start, finish, profit; | |
}; |
View knucles.cpp
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#include <bits/stdc++.h> | |
using namespace std; | |
#define int long long | |
#define what_is(a) cout << #a << " is " << a << "\n" | |
#define checker(a) cout << "checker reached " << a << "\n" | |
inline void io(){ | |
ios_base::sync_with_stdio(false); |
View minimalCost.cpp
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#include <bits/stdc++.h> | |
using namespace std; | |
#define int long long | |
#define what_is(a) cout << #a << " is " << a << "\n" | |
#define checker(a) cout << "checker reached " << a << "\n" | |
inline void io(){ | |
ios_base::sync_with_stdio(false); |
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