prashantgpt91

wget --load-cookies /tmp/cookies.txt "https://docs.google.com/uc?export=download&confirm=$(wget --quiet --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=FILEID' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=FILEID" -O FILENAME && rm -rf /tmp/cookies.txt

prashantgpt91

---
layout: default
---
{% assign posts = '' | split: '/' %}
{% for post in site.posts %}
  {% if post.queued == null %}
    {% assign posts = posts | push: post %}
  {% endif %}
{% endfor %}
{% assign totalPages = site.posts | size | minus: 1 | divided_by: 9 %}

prashantgpt91

git push https://x0v:[email protected]/x0v/x0v.github.io.git master

prashantgpt91

         git config credential.username x0v

prashantgpt91

         git init
         sudo git remote add BRANCH-NAME REPO_URL
         git checkout -b BRANCH-NAME
         git add .
         git commit -m "COMMIT MSG"
         git push REPO_URL BRANCH-NAME:BRANCH-NAME
         git pull BRANCH-NAME BRANCH-NAME

prashantgpt91

            git log -1
        
            commit 8a72148741d8d18k40fbe8fd9e0b79d0812cd478
            Author: Prashant Gupta <[email protected]>
            Date:   Tue Oct 31 08:16:01 2017 +0000

            README.md created online with Bitbucket
        
            git log -2

prashantgpt91

git push https://[email protected]/yyyy/xxxxx.git --delete branch_name

prashantgpt91

            git add -u
            git reset -- main/*
            git add .
            git commit -m "commit message"
            git push -u origin master

prashantgpt91

            git add -u
            git reset -- main/dontcheckmein.txt
            git add .
            git commit -m "commit message"
            git push -u origin master

prashantgpt91

If we do not apply a Activation function then the output signal would simply be a simple linear function.A linear function is just a polynomial of one degree. Now, a linear equation is easy to solve but they are limited in their complexity and have less power to learn complex functional mappings from data. A Neural Network without Activation function would simply be a Linear regression Model, which has limited power and does not performs good most of the times. We want our Neural Network to not just learn and compute a linear function but something more complicated than that. Also without activation function our Neural network would not be able to learn and model other complicated kinds of data such as images, videos , audio , speech etc. That is why we use Artificial Neural network techniques such as Deep learning to make sense of something complicated ,high dimensional,non-linear -big datasets, where the model has lots and lots of hidden layers in between and has a very complicated architecture which helps