niazangels

# All steps taken from https://github.com/sytelus/pcprep/tree/master/ubuntu
# Remember to to "Enroll MOK" on UEFI when rebooting 




# UNINSTALL EXISTING VERSIONS

# works for 11.8 and higher installed using deb file

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ffresize(){
for f in *.mp4 ; do ffmpeg -i "$f" -vf scale=854:480 "$f-480p.mp4" ; done
}

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# References:
# https://github.com/PrettyPrinted/youtube_video_code/blob/master/2020/12/31/How%20to%20Speed%20Up%20API%20Requests%20With%20Async%20Python/apiasync/script.py
# https://stackoverflow.com/questions/47934212/how-to-use-python-aiohttp-library-to-download-multiple-webpages
# https://pawelmhm.github.io/asyncio/python/aiohttp/2016/04/22/asyncio-aiohttp.html

import aiohttp
import aiofiles
import asyncio

URLS = [] # populate this

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from abc import ABC
from enum import Enum


class BankAccount:
    OVERDRAFT_LIMIT = -500

    def __init__(self, balance=0):
        self.balance = balance

niazangels

Mistakes I've made in training deep neural networks

1. Using a Relu activation in the last layer for classification

nn.CrossEntropyLoss() would automatically apply a softmax over the last layer.

2. Backpropagating with an optimizer whose params were initialized with a different model

Especially in Jupyter Lab.

This is particularly weird because it won't raise any errors and your loss will appear to be stable and the model will not learn anything

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# https://github.com/mstamy2/PyPDF2/issues/53
import os, shutil, tempfile
from pathlib import Path
# Things from the subprocess module don't rely on the shell unless you
# explicitly ask for it and can accept a pre-split list of arguments,
# making calling subprocesses much safer.
# (If you really do need to split quoted stuff, use shlex.split() instead)
from subprocess import check_call

# [...]

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Twitter Official Consumer Key

Twitter for Android

type:            PIN
Consumer key:    3nVuSoBZnx6U4vzUxf5w
Consumer secret: Bcs59EFbbsdF6Sl9Ng71smgStWEGwXXKSjYvPVt7qys

Twitter for iPhone

type:            PIN

Consumer key: IQKbtAYlXLripLGPWd0HUA

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cmake -D CMAKE_BUILD_TYPE=RELEASE \
-D CMAKE_INSTALL_PREFIX=/usr/local \
-D INSTALL_PYTHON_EXAMPLES=ON \
-D INSTALL_C_EXAMPLES=OFF \
-D OPENCV_ENABLE_NONFREE=ON \
-D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib/modules \
-D PYTHON_EXECUTABLE=~/.local/share/virtualenvs/kaggle-3VckuriQ/bin/python \
-D PYTHON_NUMPY_INCLUDE_DIR=~/.local/share/virtualenvs/kaggle-3VckuriQ/lib/python3.6/site-packages/numpy/core/include/ \
-D BUILD_opencv_python3=yes -D PYTHON_LIBRARY=/home/niyas/anaconda3/lib/libpython3.6m.so -D BUILD_EXAMPLES=ON ..

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sample = np.random.choice(processed_data.index, size=int(len(processed_data)*0.9), replace=False)
train_data, test_data = processed_data.iloc[sample], processed_data.drop(sample)