Ninja saas-coder
saas-coder
/ GradientDescent.hpp
Last active
December 13, 2020 14:14
Implementing Gradient Descent for linear and logistic regression
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| #include <armadillo> | |
| #include <bits/stdc++.h> | |
| #include <conio.h> | |
| using namespace std; | |
| double LeastSquaesCost(const mat& X, const mat& y, const mat& parameters) | |
| { | |
| vec tmp(X * parameters - y); | |
| tmp = dot(tmp, tmp); | |
| double s = sum(tmp); |
saas-coder
/ QuasiNewton.hpp
Created
December 15, 2020 14:44
Quasi Newton : BFGS and BROYDEN and DFP and SR1 for regression
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| void quasinewton(const mat& X, | |
| const mat& y, | |
| mat& parameters, | |
| double computeCost(const mat& X, const mat& y, const mat& parameters), // LeastSquaesCost or logisticCost | |
| vec computeGradient(const mat& X, const mat& y, const mat& parameters), // LeastSquaesGradient or logisticGradient | |
| mat computeHessian(const mat& X, const mat& y, const mat& parameters), // logisticHessian or | |
| string method = "BFGS", // BFGS or BROYDEN or DFP or SR1 | |
| string costs_file = "costs.out", | |
| string parameters_file = "parameters.out", | |
| string step = "armijo", // double as string like "0.01" by default armijo rule |
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saas-coder
/ telegram-kaggle.py
Last active
April 19, 2021 11:12
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| # installation | |
| !pip install knockknock #For sending message to telegram | |
| # Importation | |
| from knockknock import telegram_sender | |
| from kaggle_secrets import UserSecretsClient | |
| user_secrets = UserSecretsClient() | |
| token = user_secrets.get_secret("token") | |
| chat_id = user_secrets.get_secret("chat_id") |
saas-coder
/ lacuna.py
Last active
April 28, 2021 21:11
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| urls = """https://api.zindi.africa/v1/competitions/lacuna-correct-field-detection-challenge/files/sentinel-2-part1.zip | |
| https://api.zindi.africa/v1/competitions/lacuna-correct-field-detection-challenge/files/extra_train-planet-dec17.zip | |
| https://api.zindi.africa/v1/competitions/lacuna-correct-field-detection-challenge/files/extra_train-planet-jun18.zip | |
| https://api.zindi.africa/v1/competitions/lacuna-correct-field-detection-challenge/files/starter-notebook.ipynb | |
| https://api.zindi.africa/v1/competitions/lacuna-correct-field-detection-challenge/files/extra_train-sentinel.zip | |
| https://api.zindi.africa/v1/competitions/lacuna-correct-field-detection-challenge/files/sentinel_for_points_collected_in_2015.zip | |
| https://api.zindi.africa/v1/competitions/lacuna-correct-field-detection-challenge/files/extra_train-planet-jun17.zip | |
| https://api.zindi.africa/v1/competitions/lacuna-correct-field-detection-challenge/files/extra_train-planet-dec18.zip | |
| https://api.zindi.africa/v1/competitions/lacuna-correct-field-detection-challenge/f |
saas-coder
/ idling-algo.py
Created
February 11, 2023 15:57
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| import numpy as np | |
| from scipy.fftpack import fft | |
| def vehicle_condition_detection(acc_info, g, h, h_prime, h_1, h_2, T): | |
| time = 0 | |
| vehicle_condition = "Unknown" | |
| while True: | |
| for t in range(len(acc_info)): | |
| Ax, Ay, Az = acc_info[t] |
saas-coder
/ spect+resnet.py
Created
February 11, 2023 16:01
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| import librosa | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| import tensorflow as tf | |
| def plot_spectrogram(sound, sr): | |
| S = librosa.feature.melspectrogram(sound, sr=sr) | |
| log_S = librosa.power_to_db(S, ref=np.max) | |
| plt.figure(figsize=(12, 4)) | |
| librosa.display.specshow(log_S, sr=sr, x_axis='time', y_axis='mel') |
saas-coder
/ gist:10475782d3bece97ccb88ddd5bd8ed2d
Created
March 20, 2023 15:02
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| <?xml version="1.0" encoding="UTF-8"?> | |
| <Response> | |
| <Say voice="woman" language="es-ES"> Hola cómo estás </Say> | |
| </Response> |
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