Snippets Collections
# Visualize one training batch
for images, labels in train_data_loader:
    fig, ax = plt.subplots(figsize = (10, 10))
    ax.set_xticks([])
    ax.set_yticks([])
    ax.imshow(make_grid(images, 4).permute(1,2,0))
    break
ūüĎ®‚ÄćūüíĽ boilerplate code


Hugo:
hugo new content/posts/new-car.md
hugo new site my-portfolio-example
# defaultTheme = "dark"

Git push:
# Example of the commands and how they apply to my project
cd my-portfolio-example
git init
git remote add origin git@gitlab.com/cardenas88karl/my-portfolio-example
git add -A
git commit -m "Initial commit"
git push -u origin master

# when pushing from a new branch
git checkout -b <branch>
git add .
git commit -m "comment"
git push -u origin <branch>

# Bring a local folder to remote git repo
// https://superuser.com/a/1412081
 $ git init
 $ git add .
 $ git commit -m "First commit"
 $ git remote add origin <remote repository URL>
 # Sets the new remote
 $ git remote -v
 # Verifies the new remote URL

# create pandas df from python dict
data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
pd.DataFrame.from_dict(data)


Drive mount:
from google.colab import drive
drive.mount("/content/gdrive")

python essential:
#!/usr/bin/env python

python virtual env:
pip install -r requirements.txt
mkdir TextGenEnv
virtualenv TextGenEnv
TextGenEnv\Scripts\activate (for bash source ./Scripts/activate)
pip install -r requirements.txt
python -m scikit-learn --version


<p align="center">
<img width="300" height="250" src="https://i.ibb.co/sHF9d7k/Smart-GForms.png">
</p>

python encoder_train.py name data/SV2TTS/encoder/ --no_visdom
data = np.transpose(data, axes=[3, 2, 1, 0])


vivek.poddar@gmail.com


cliche


g++ -o rp linear_search.cpp


<p align="center">
<img src="../imgs/pointer.png">
</p>
To insert tab space between two words/sentences I usually use
&emsp; and &ensp;


grit
fast learn
fast fail
intelectual decision(head quater at pakistan)
passion
![](https://github.com/SauravMaheshkar/siim-covid19/blob/main/assets/SIIM-COVID19%20Github%20Banner.png?raw=true)
collage, professional, modern,executive

---
layout: post
title: Flake it till you make it
subtitle: Excerpt from Soulshaping by Jeff Brown
cover-img: /assets/img/path.jpg
thumbnail-img: /assets/img/thumb.png
share-img: /assets/img/path.jpg
tags: [books, test]
---



-------Pandas---------
show all row and columns:
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
------------------------------------------------


+++++++++Center text in markdown+++++++++
<h1 align="center">Crima</h1>
+++++++++++++++++++++++++++++++++++++


~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
i think it would be great to have - [ ] if unchecked and - [x]if checked in lists.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


_______________Windows terminal EXE________________________
wt.exe
______________________________________________________


npx localtunnel --port 8501


I have been watching some deep Learning implementations, But don't really understand why the model is taking two inputs, `X_train, assets_train` for training? Why can't someone just train the model with the provided training data, is it really necessary to include `asset_details.csv`?
**It would be really helpful if you can answer. Thank you.**


coomer






1e-4 = 0.0001


Shift+Ctrl+C to add a checkbox
Ctrl+B to bold
Ctrl+I to italic
Ctrl+U to underline
Shift+Ctrl+S.... you know the story




https://github.com/AlexeyAB/darknet
https://github.com/DarkStar1997/darknet-cpp-app


As @slawekbiel said ` Likewise restarting the kernel picks up the new version.`
1. After doing `!pip -v install numpy==1.20.0`
2. Do `Run` --> `restart and clear cell output`/ I understand that
3. And then run the code,
```
import numpy as np
print(np.__version__)
arr = np.zeros((1,2)) + np.zeros((3,2,1))
np.broadcast_shapes((1, 2),(3,2,1))
# 1.20.0
# (3, 2, 2)
```
<p align="center">
<img src="https://i.imgur.com/ZatsYza.png">
</p>

https://i.imgur.com/ZatsYza.png
<!doctype html>

<html lang="en">
<head>
  <meta charset="utf-8">
  <meta name="viewport" content="width=device-width, initial-scale=1">

  <title></title>

	/* CSS STYLESHEET */

	<link rel="stylesheet" href="styles.css">

	/* BULMA */

 	<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bulma@0.9.3/css/bulma.min.css">
      
	/* FONTAWESOME */
      
	<script src="https://use.fontawesome.com/releases/v5.15.4/js/all.js" data-auto-	a11y="true"></script>


</head>

<body>
      
	/* JAVASCRIPT SCRIPTS /*
    
	<script src="script.js"></script>

</body>
</html>
star

Wed Feb 09 2022 18:13:34 GMT+0000 (UTC) https://www.kaggle.com/jainamshah17/pytorch-starter-image-classification

#boilerplate #python #grid
star

Sat Feb 05 2022 06:32:42 GMT+0000 (UTC)

#boilerplate

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