In unsupervised learning, we are provided with a dataset and nothing else. There is no outputs, parameters or anything to distinguish the given data. Our aim is to let the machine to learn or create a grouping/classification on its own. Unsupervised learning is comparatively difficult with respect to supervised learning. Consider social networking sites, based on our actions they are filling our feed with posts/media that we would prefer, suggests people we want to follow and a lot of things. These kinds of solutions are done using unsupervised learning. In the figure, social media users are grouped by machine based on some factors which are unknown to the programmer. This could be a simple example of unsupervised learning.
In this post we will cover topics; Starting a server using Python Flask. Accessing server in Local Network. Adding a Port Forwarding rule in NAT settings. Accessing server in Internet via public IP. Difference between static IP and dynamic IP. Step 1 :- As the first step, we need to setup a server on our system.A server exposes your code to a particular port.Some examples are Apache Tomcat, Spring boot (inbuilt), Python Django (inbuilt), Nginx. Here we have a simple server in Python Flask. For a GET request in root path the server returns a "Hello World!".That's it. Going to start the server on my local IP address(192.168.1.105) at default flask port(5000) using below commands, $export FLASK_APP=flaskTest.py $flask run --host=192.168.1.105 Step 2 :- For security purpose all ports for external communication is closed by router's firewall by default. So no communication can be done to outside world. For same reason our server won't be
This article will discuss the following topics, Blogger's REST APIs. Google's OAuth 2.0 playground. Accessing spreadsheet in Python. Creating blogger posts via Python. An experiment to automate blog post creation when you have structured data. I was searching for IFSC codes for some bank transactions and came across Reserve Bank's website, which has a list of Excel files containing Bank Codes, Contact Info and related details of each bank's branch. This time I will be looking towards Bharat co-operative bank of Mumbai. Here is how the corresponding data looks like. In the above picture, each row represents lots of details about each branch of the Bank. Let's think of creating a list of blog posts where each post gives IFSC codes of a particular branch along with address and contact details. As the first step, I have created a blog in blogger. In the Blogger dashboard, please also note the parameter called blog ID which is a kind of unique identifier
Setting up a headless OS is always painful and imagine the situation to do it without a monitor or keyboard. Here in this post, I will demonstrate how to setup Ubuntu Server in a Raspberry Pi and connect to WiFi with a static IP. The process includes the following steps, Installation of Raspberry Pi Imager Flash Ubuntu Server to SD Card Initial setup of Ubuntu Server on Raspberry Pi Configuring Static IP in Ubuntu Server's netplan network manager. Raspberry Pi Imager Raspberry Pi Imager is an SDcard burner program from the Raspberry Pi foundation aimed to make installation of different OSes in the Pi easier. You can navigate to the below link to download and install Pi Imager for your operating system. Source: https://www.raspberrypi.org/downloads/ Flash the SD card with Ubuntu Server Connect an SD card (preferably with storage 16GB or more) to your laptop/PC and launch Pi Imager application. From the listed Operating Systems, choose Ubuntu Server 64 bit version. I choose the 6
***** Work In Progress ******* Ever since I entered to IT industry, I was hearing about data science machine learning and the miracles happened because of these. On curiosity, I too have started learning some the concepts on these areas. As the first step, I have enrolled in Andrew N G's Machine Learning course. I will be sharing things I have learned in this blog and consider this post as an Index for my learning. Good Luck!!! Definition of Machine Learning Supervised Learning Linear Regression Cost Function Gradient Descent Unsupervised Learning
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