Geek-a-Byte

Awesome Courses

Introduction

There is a lot of hidden treasure lying within university pages scattered across the internet. This list is an attempt to bring to light those awesome courses which make their high-quality material i.e. assignments, lectures, notes, readings & examinations available online for free.

Table of Contents

Geek-a-Byte

## Follow this link for further updates to Github Desktop for Ubuntu https://github.com/shiftkey/desktop/releases/latest
# UPDATE (2022-11-07): Thanks to Sxvxgee's message, the updated code is as follows

sudo wget https://github.com/shiftkey/desktop/releases/download/release-3.1.1-linux1/GitHubDesktop-linux-3.1.1-linux1.deb
### Uncomment below line if you have not installed gdebi-core before
# sudo apt-get install gdebi-core 
sudo gdebi GitHubDesktop-linux-3.1.1-linux1.deb


# UPDATE (2021-10-18): Thanks to Amin Yahyaabadi's message, the updated code is as follows

Geek-a-Byte

# https://stackoverflow.com/questions/58935672/i-get-brokenpipeerror-errno-32-broken-pipe-error-in-python
from requests.exceptions import ConnectionError

def retry_on_connectionerror(f, max_retries=5):
  retries = 0
  while retries < max_retries:
    try:
      return f()
    except ConnectionError:
      retries += 1

Geek-a-Byte

!pip install nexusformat # one time run

import nexusformat.nexus as nx
f = nx.nxload('/content/sample.h5')
print(f.tree)

## or

global_model = load_model('/content/sample.h5')
global_model.summary()

Geek-a-Byte

import requests

def download_file_from_google_drive(id, destination):
    URL = "https://docs.google.com/uc?export=download"

    session = requests.Session()

    response = session.get(URL, params = { 'id' : id }, stream = True)
    token = get_confirm_token(response)

Geek-a-Byte

!pip install gdown==3.6.0
my_file_id = "1-5qd5G2e9Y5AvgHRkeXncNvgcC-N783J"
!gdown https://drive.google.com/uc?id={my_file_id}

Geek-a-Byte

import tensorflow as tf
from tensorflow.keras.models import load_model

from google.colab import drive
drive.mount('/content/gdrive')

model_save_name = "test.h5"
path = F"/content/cervical_cancer_global_model.h5"
%cp "{path}" "/content/gdrive/MyDrive/Thesis_A_10/global_model_weights/{model_save_name}" 

Geek-a-Byte

%%writefile app.py
from __future__ import print_function

import streamlit as st
from googleapiclient.errors import HttpError
from googleapiclient.http import MediaFileUpload
from googleapiclient.discovery import build
from oauth2client.service_account import ServiceAccountCredentials
import os

Geek-a-Byte

# https://www.youtube.com/watch?v=MUD-pBOnvdo&t=8s&ab_channel=1littlecoder

#install streamlit, one time execution
!pip install streamlit

#import streamlit
import streamlit as st

# Commented out IPython magic to ensure Python compatibility.
# %%writefile app.py

Geek-a-Byte

!pip install pyforest
!pip install lazypredict

import pyforest
import lazypredict
from lazypredict.Supervised import LazyClassifier

clf = LazyClassifier(verbose=0, predictions=True, ignore_warnings=False, custom_metric=None)
models, predictions = clf.fit(X_train, X_test, y_train, y_test)