Sentiment Analysis using Machine Learning
Negotiated
Skills Development is a module that provides us the opportunity to negotiate
and agree on a specific area of study which enables us to learn or enhance a
new set of skills.
Aim: To develop a machine learning model that analyzes sentiment of the texts.
Objectives:
- To research on theory and principles of machine learning
- To research on Natural Language Processing (NLP) and evaluate statistical techniques
- To explore new programming language python in regards to data analysis
- To formulate a machine learning model that analyzes sentiment of the texts
For this
module I have chosen to formulate a machine learning model that can be used to analyze
the sentiment of the text. Sentiment analysis allows to gain an overview of the
opinions of people. Presently, people post lots of things regarding their
opinions and views in social sites. Using sentiment analysis, monitoring and
analyzing those posts, tweets and reviews have been made easier and quicker.
Several organizations are aware of the purposefulness of sentiment analysis
that it has been in practice to extract insights from data and understand
attitudes of customers/people so that the organizational activities can be
changed accordingly. The model aims to analyze the reviews are positive or
negative that have been given by audiences.
The model
will be developed after I brush up my skills on machine learning and gain new
skills regarding python language and Natural language Processing (NLP)
techniques. The first thing is to research about theory and principles of
machine learning explaining why machine learning is needed and its importance. Secondly, I will explore about statistical techniques of NLP along with machine
learning algorithm required for the sentiment analysis. Afterwards, I will
learn how to code these things in Python, which will enable me to create a
model. The model will be developed in the basis of secondary data. The dataset is downloaded from Kaggle where real time reviews of imdb is included.
The Negotiated Skill Development Contract(NSDC) that has been agreed for the module to be marked against.
The Negotiated Skill Development Contract(NSDC) that has been agreed for the module to be marked against.
Sentiment Analysis using Machine Learning
Student Name
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Priyanka
Neupane
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Student ID
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77210282
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Course
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MSc Creative
Technology
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Title/Grade
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Description
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In what format will
you evidence your Learning outcome?
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Date of completion
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To
research on theory and principles of machine learning
(20 %)
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I will
follow through research, based on articles, journals for clear understanding
of machine learning algorithms and its implementation.
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The
underlying theory will be described and stated on the blog as well as
implemented throughout the development of the model.
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10 November 2019
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To
understand Natural Language Processing (NLP) and statistical
techniques (20 %)
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I will
research and comprehend NLP algorithm, its processes, and its uses in the
present context.
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The
algorithm, processes and statistical techniques need to be followed for the
analysis of the data in real time. All the stages and processes will be
documented.
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20 November 2019
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To explore
new programming language python in regards to data analysis (25 %)
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Since I
am new to python, I will look through the tutorials and videos to construct a
model through python platform.
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The
model will be developed and coded using python and demonstration will be
represented on my blog.
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19 December 2019
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To cohere
with the requirements of Leeds Beckett University (10 %)
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Mapping the
guidelines and requirements provided by the University will ensure quality of
the model. Supervision and interaction with tutor will forge to meet the
valued standard of the product.
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The exemplary
will validate that requirements are met.
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20 December 2019
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To
formulate a machine learning model that includes above mentioned skills (25 %)
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Skills
acquired from learning a new programming language will be incorporated as a
main platform to generate a machine learning model. The model will be
produced by supervised learning algorithm incorporating Natural Language processing (NLP) and its
underlying statistical and text mining techniques. The model will focus on
sentiment analysis as a part of NLP.
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The whole
process of the model will be documented by means of blog and demonstrated
over presentation.
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1 January 2019
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