A detailed explanation of using AWS EC2 services for free

Pre-requisite: AWS for Machine Learning — Part 2
A detailed explanation of creating an AWS account and using AWS services for free

After creating a free account on AWS and completing the signup process as shown in the previous article we end up with a screen like below.


A detailed explanation of creating an AWS account and using AWS services for free

Pre-requisite: AWS for Machine Learning — Part 1
Cloud computing for dummies. A brief layman understandable explanation for anyone. A must for any budding developers/tester.

📄Contents.

1. Cloud Computing.
2. What is AWS?
3. AWS for machine learning

2.1 Definition of AWS

As Amazon explains in their documentation.

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers — including the fastest-growing startups, largest enterprises, and leading government agencies — are using AWS to lower costs, become more agile, and innovate faster.

2.2. Fields using AWS.

Any application which would require computing


Cloud computing for dummies. A brief layman understandable explanation for anyone. A must for any budding developers/tester.

📄Contents.

1. Cloud Computing.
2. What is AWS?
3. AWS for machine learning

1.1 What is Cloud Computing?

Before the concept of cloud computing came into the picture back then even if a website needs to be hosted companies had to buy huge servers and maintain them. It was a huge cost and inefficient workforce diversion for the companies which wanted to focus on the actual task at hand rather than the maintaining of these servers.

Some other companies saw this as an opportunity which went ahead and bought these huge servers and had a huge collection of servers and rented them out to other companies.


AIMLArtificial Intelligence Markup Language (Rule-based Chatbots)

Pre-requisite: So you want to build a chatbot from scratch? (Chatbots Part-1)

AIML stands for Artificial Intelligence Markup Language. AIML was developed by the Alicebot free software community and Dr Richard S. Wallace during 1995–2000. AIML is used to create or customize Alicebot which is a chat-box application based on A.L.I.C.E. (Artificial Linguistic Internet Computer Entity) free software.

AIML Tags:

There are around 14 tags that we normally use in AIML. There are much more present and there are differences in AIML 1.0 and 2.0 …


Chatbot Types: Rule-Based Chatbots and AI-Based Chatbots

source

Introduction

A Chatbot (sometimes referred to as a chatterbot) is a computer program that attempts to simulate the conversation or “chatter” of a human being via text or voice interactions.
Basically, it receives the command from the user and responds back in a satisfactory way to the user which results in the completion of the action or conversation initiated by either of them.

Usages

“Its usage is potentially endless” many sectors like E-commerce, Finances, HR, Healthcare each and every place where there is a need for certain information to be responded back or certain action…


The steps to be taken before applying for machine learning and AI related jobs. The roadmap, required skill sets, materials, are also linked below.

This is one of the most FAQ where aspiring people who are new in this field ask me on a frequent basis so let us get on with it.

Why AI or machine learning related jobs?

Because it is much more interesting than the other traditional coding and non-coding related jobs and the next reason is said by the world economic forum (source)that is….


NLP libraries — when, which and where to use them. NLTK, TextBlob, Spacy, CoreNLP, Genism, Polyglot.

One of the main questions that arise while building an NLP engine is “Which library should I use for text processing?” since there are many in the market and also “What is the need for the usage of NLP libraries?” these two are addressed here and helps you take the right step in the path for building NLP engine from scratch on your own.

This article is a part of an ongoing series: Part-1

“What is the need for the usage of NLP libraries?”

Natural language processing (NLP) is getting very popular today. NLP…


Difference between NLP, NLU, NLG and the possible things which can be achieved when implementing an NLP engine for chatbots.

It is quite common to confuse specific terms in this fast-moving field of Machine Learning and Artificial Intelligence. The above is the same case where the three words are interchanged as pleased.

Now let us get down with three words:

  1. NLP — Natural Language “Processing”
  2. NLU — Natural Language “Understanding”
  3. NLG — Natural Language “Generation”

If I need to say it in a mathematical way it could be said as the combination of NLU and NLG will result in an…


Machine Learning implementation example in 5 minutes. Implement a multiple linear regression model in python( Part 3).

Linear Regression

Prerequisite: Linear Regression (Part 1)

Since the theory is discussed previously, let us now kick off with actual implementation. There are different datasets available but let us implement it with our own data sets. A simple linear regression has dependent variables (Y) and independent variables (X).

Step-1: Prepare the datasets


Machine Learning implementation example in 5 minutes(In Part 3). Implement a machine learning model in linear regression in python.

Linear Regression

Prerequisite: Machine Learning Types and list of algorithms

Linear Regression is one of the most common, some 200 years old and most easily understandable in statistics and machine learning. As explained in the previous post it comes under predictive modelling. Predictive modelling is a kind of modelling here the possible output(Y) for the given input(X) is predicted based on the previous data or values.

Types

  1. Simple Linear Regression: It is characterized by one independent variable. Consider the price of the house

Chethan Kumar GN

Data Scientist @IndianMoney.com

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