Skip to content

Instantly share code, notes, and snippets.

View alik604's full-sized avatar
Full time student

K. Ali Pardhan alik604

Full time student
View GitHub Profile
alik604 /
Last active April 9, 2022 17:01
FFMPEG to reencode (encode) entire windows directory with GPU or x265

FFMPEG to reencode (encode) entire windows directory with GPU or x265


for %i in (*.mp4) do ffmpeg -i "%i" -c:v libx265 -vtag hvc1 -preset fast "%~ni_265.mp4"

ffmpeg -i input.mp4 -c:v libx265 -vtag hvc1 -preset fast input_compressed.mp4

Nvidia GPU

for %i in (*.mp4) do ffmpeg -i "%i" -c:v hevc_nvenc -preset fast "%~ni_nvda.mp4"

alik604 /
Created June 10, 2021 22:46
PCA vs IncrementalPCA
import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import load_digits
from sklearn.decomposition import PCA, IncrementalPCA
iris = load_iris()
X =
y =

Python & Machine Learning Hello world

Quickly get up to speed

Software setup

Use Python 3.8.*. No point in 3.9, however it should be fine.

Run these to test if install is successful, and install some important packages. Please follow the errors as they come, one will ask the user to install C++ build tools, if not already installed (see below). This will take several minutes, as the dependencies are a few GBs. You must be off VPN, or set-proxy, as shown below.

alik604 / starred repo
Last active January 28, 2024 15:07
Open all starred GitHub repositories in new tab - Open every starred GitHub repo in chrome, with python
import requests
import json
import webbrowser
USER = "alik604"
chrome_path = 'C:/Program Files (x86)/Google/Chrome/Application/chrome.exe %s'
# Change to your OS -
req = requests.get('' + USER + '/starred?per_page=100')
# ?page=2&per_page=100 # page is not working, first result is always the same
alik604 /
Last active August 24, 2020 23:41 — forked from tartakynov/
Fourier Extrapolation in Python
import numpy as np
import pylab as pl
from numpy import fft
def fourierExtrapolation(x, n_predict):
n = x.size
n_harm = 10 # number of harmonics in model
t = np.arange(0, n)
p = np.polyfit(t, x, 1) # find linear trend in x
!pip install mnist
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn import metrics
import mnist
# from hmmlearn.hmm import GaussianHMM, MultinomialHMM
X_train = mnist.train_images()
import urllib.parse as parse
url = ""
if 'url' not in globals():
print("Enter URL to parse")
url = input()
def printDict(data):
for x in data:
alik604 / build_dataset
Created July 28, 2020 01:17
# make dataset to input
def build_dataset(time_series, seq_length):
dataX = []
dataY = []
for i in range(0, len(time_series) - seq_length):
_x = time_series[i:i + seq_length, :]
_y = time_series[i + seq_length, [-1]] # Next close price
print(_x, "->", _y)
alik604 / visualizing data in 2d and
Last active October 24, 2023 22:40
Quickly visualize your data in 2d and 3d with PCA and TSNE (t-sne)
# imports from matplotlib import pyplot as plt
from matplotlib import pyplot as plt
import pylab
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d import proj3d
%matplotlib inline
%pylab inline
from sklearn.manifold import TSNE
from sklear.decomposition import PCA
alik604 /
Last active July 1, 2020 00:34
boiler plate for jupyter notebook on Data Science or Machine Learning
!pip install scikit-plot
!pip install catboost
!pip install mlxtend
!pip install yfinance
!pip install pyod
import pyod
import yfinance
import xgboost #