Chatbot Development with Python NLTK

Chatbots are intelligent agents that engage in a conversation with the humans in order to answer user queries on a certain topic. Amazon’s Alexa, Apple’s Siri and Microsoft’s Cortana are some of the examples of chatbots.

Depending upon the functionality, chatbots can be divided into three categories: General purpose chatbots, task-oriented chatbots, and hybrid chatbots. General purpose chatbots are the chatbots that conduct a general discussion with the user (not on any specific topic). Task-oriented chatbots, on the other hand, are designed to perform specialized tasks, for example, to serve as online ticket reservation system or pizza delivery system, etc. Finally, hybrid chatbots are designed for both general and task-oriented discussions.

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Scraping Tweets and Performing Sentiment Analysis

Sentiment Analysis is a special case of text classification where users’ opinions or sentiments regarding a product are classified into predefined categories such as positive, negative, neutral etc.  Public sentiments can then be used for corporate decision making regarding a product which is being liked or disliked by the public.

Both rule-based and statistical techniques have been developed for sentimental analysis.  With the advancements in Machine Learning and natural language processing techniques, Sentiment Analysis techniques have improved a lot.

In this tutorial, you will see how Sentiment Analysis can be performed on live Twitter data. The tutorial is divided into two major sections: Scraping Tweets from Twitter and Performing Sentiment Analysis.

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Twitter API: Extracting Tweets with Specific Phrase

Twitter has been a good source for Data Mining. Many data scientists and analytics companies collect tweets and analyse them to understand people’s opinion about some matters.

In this tutorial, you will learn how to use Twitter API and Python Tweepy library to search for a word or phrase and extract tweets that include it and print the results.

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Searching GitHub Using Python & GitHub API

GitHub is a web-based hosting service for version control using Git. It is mostly used for storing and sharing computer source code. It offers all of the distributed version control and source code management functionality of Git as well as adding its own features.

GitHub stores more than 3 million repositories with more than 1.7 million developers using it daily. With so much data, it can be quite daunting at first to find information one needs or do repetitive tasks, and that is when GitHub API comes handy.

In this tutorial, you are going to learn how to use GitHub API to search for repositories and files that much particular keywords(s) and retrieve their URLs using Python. You will learn also how to download files or a specific folder from a GitHub repository.

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Amazon S3 with Python Boto3 Library

Amazon S3 is the Simple Storage Service provided by Amazon Web Services (AWS) for object based file storage. With the increase of Big Data Applications and cloud computing, it is absolutely necessary that all the “big data” shall be stored on the cloud for easy processing over the cloud applications.

In this tutorial, you will learn how to use Amazon S3 service via the Python library Boto3. You will learn how to create S3 Buckets and Folders, and how to upload and access files to and from S3 buckets. Eventually, you will have a Python code that you can run on EC2 instance and access your data on the cloud while it is stored on the cloud.

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Extracting YouTube Comments with YouTube API & Python

YouTube is the world’s largest video-sharing site with about 1.9 billion monthly active users. People use it to share info, teach, entertain, advertise and much more.

So YouTube has so much data that one can utilize to carry out research and analysis. For example, extracting YouTube video comments can be useful to run Sentiment Analysis and other Natural Language Processing tasks. YouTube API enables you to search for videos matching specific search criteria.

In this tutorial, you will learn how to extract comments from YouTube videos and store them in a CSV file using Python. It will cover setting up a project on Google console, enabling the necessary YouTube API and finally writing the script that interacts with the YouTube API.

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Google Places API: Extracting Location Data & Reviews

Google places API allows developers to access a wealth of information from Google’s database for over 100 million places including location data, contact information, user ratings and reviews and more.

In this tutorial, you will learn how to create a reusable class to read and extract location related information from Google Places API. This tutorial will help you if you want to extract business’s name, address, phone number, website, and reviews.

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AWS EC2 Management with Python Boto3 – Create, Monitor & Delete EC2 Instances

Amazon Web Services is one of the world’s leading cloud service provider. among many services, Elastic Compute Cloud (EC2) allows users to rent virtual computers over the AWS.

In this tutorial, you will learn how to monitor, create and manage EC2 instances using Python. AWS has launched the Python library called Boto 3, which is a Python SDK for AWS resources. This tutorial will cover how to install, configure and get started with Boto3 library for your AWS account. This tutorial will also cover how to start, stop, monitor, create and terminate Amazon EC2 instances using Python programs.

Finally, the tutorial provides Python code to easily see EC2 instances and key information in tabular format and ways to query EC2 instances for dynamic access and monitoring.

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Google Colab: Using GPU for Deep Learning

In this series of tutorials, you will learn how to use a free resource called Colaboratory given out by Google and build a simple yet sophisticated Neural Machine Translation model.

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Sublime Text: Efficient Python Editor

While the environment in which you write your code is not that important and it is just a personal preference, you might like to know that throughout my Scrapy course, I use a robust text editor called Sublime Text.

Sublime Text is light-weight, fast and easy to get the hang off text editor that you can use for writing Python scripts. It also supports almost all other programming languages. Let’s see how to make the best use of it. Continue reading “Sublime Text: Efficient Python Editor”