Some Report

A Project Plan

On

Analysis on the growth of Indian Economy

Submitted to

Amity University Uttar Pradesh

Amity of School of Engineering & Technology

Noida, Uttar Pradesh

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF

BACHELOR OF TECHNOLOGY IN COMPUTER SCIENCE AND ENGINEERING

2012- 2016

Under guidance of: Submitted by:

Mrs. Rajni Sehgal Krishna Kumar

Associate Professor A2305212243

4th year, 7th semester

CERTIFICATE

On the basis of declaration submitted by Krishna Kumar of B.Tech CSE, I hereby

certify that the project titled “Predictive Analysis on Indian Economy” which is

submitted to Department of computer Science, Amity University, Uttar Pradesh, Noida,

in partial fulfillment of the requirement for the award of the degree of Bachelor of

Technology in Computer Science and Engineering, is an original contribution with

existing knowledge and faithful record of work carried out by her under my guidance

and supervision.

To the best of my knowledge this work has not been submitted in part or full for any

degree or diploma to this university or any other.

Date: ______________________ ____________________________

Ms. Rajni Sehgal

Department of Computer Science and

Engineering

ASET, Noida

ii

DECLARATION

I, Krishna Kumar, student of B.tech (CSE) hereby declare that the project title

“Predictive Analysis on Indian Economy” which is submitted by me to Department of

CSE, Amity School of Engineering and Technology, Amity University Uttar Pradesh,

Noida, in partial fulfillment of requirement for the award of the degree of Bachelor of

Technology in CSE, has not been previously formed the basis for the award of any

degree, diploma or other similar title or recognition.

Date: _____________________ _____________________

Krishna Kumar

A2305212243

7CSE-4 (2012-2016)

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TABLE OF CONTENTS

S.No Contents Page No.

1. Introduction 1

1.1 Purpose of Plan

1.2 Background Information/ Available Alternatives

1.3 Project Goals and Objectives

2. Scope 3

2.1 Scope Definition

2.2 Project Budget

3. Constraints 4

3.1 Project Constraints

4. Project Management Approach 5

4.1 Project Timeline

4.2 Project Roles and Responsibilities

5. Risk Assessment 6

5.1 Project Risk Assessment

6. Literature Review 7

1. INTRODUCTION.

1.1 Purpose of Plan

In order to apply predictive analysis on the Indian Economy, we would require

necessary data sets in order to pull in the required raw data. Once we retrieve the data

sets, we would require to clean the data in order to be able to perform Exploratory Data

Analysis to get the look and feel of how the data presents itself. Once we’re done with

EDA, we will move on to the more complex part of determining which statistical model

would work best for our given data set. Once we find a suitable data model, we would

able to infer and henceforth predict how the Economy has changed over the past into the

present, and hopefully we will be able to predict how it will be affected in the future.

1.2 Background Information/Available Alternatives

The ‘economic liberalization in India’ refers to the going in the recent times economic

liberalization, which had its start in 1991, regarding the country's economic policies,

with one of its goals of making the economy of the country more oriented towards the

market and expand the role of private and foreign investment in a more rigorous

manner. To the point changes include a reduction in import tariffs, also deregulation of

markets, reducing taxes, and more of foreign investment. Liberalization has been given

credit by its components for the high economic growth recorded by the country in the

time periods of 1990s and 2000s. The opponents have blamed it for increased poverty,

inequality and economic degradation.

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2. GOALS AND OBJECTIVES

2.1 Project Goals and Objectives

Analyze data sets of key Indicators of the change in Economy.

Infer past shifts through a time-series plot

Identify the type of classification problem and apply necessary machine learning

algorithms.

Predict upcoming values of GDP using the machine learning techniques

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3. SCOPE

3.1 Scope Definition

The project will examine GDP data from a government website, after performing data

analysis on the data, we will be able to create python modules which will perform

induvial functions of applying required machine learning algorithm. The end result

would be a prediction outcome that will be obtained from one of the methods of the

algorithm.

3.2 Scope Budget

The only resource considered for the scope budget should be Time. Everything else is

being performed by Open Source tools.

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4. CONSTRAINTS

4.1 Project Constraints

Data obtained is not of sufficient measure, for more accurate predictions we

need increased amounts of data.

Key Indicators are variable in nature; they cannot be solely relied. There are

many innate factors that affect GDP in different ways.

Data visualizing is very mundane as we cannot expect outliers within the data.

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5. PROJECT MANAGEMENT APPROACH

5.1 Project Timeline

PERIOD RECOMMENDED

COMPLETION

Mid of September Topic Decided

Started Project Planning

Goals & Objectives figured out

Analyzing the problem/topic

Beginning of October Started the literature review. Reading different research papers related to the topic.

Started obtaining data, cleaning it and applying Exploratory Data Analysis

October end Detailed data analysis. Extensive data visualization.

November Attempt to classify the problem to find an appropriate machine algorithm

Mid November Apply machine learning algorithm and find desired output.

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6. RISK ASSESSMENT

Risk Assessment is an intrinsic part of software development and prepares the organization for future costs and failures which can occur. Risk analysis or assessment is not about making large amounts of paperwork, but instead it is about distinguishing sensible measures to control the risks in our project. One of the best modes to battle risks is to form a broad plan which can prevent the occurrence of failure. Expected problems have the advantage of having preset solutions. Unexpected problems tend to be very problematic since there is no planned method of resolving them.

We have not used any fixed rules for planning risk assessment or analysis on our project; instead we have followed some general principles.

For ensuring that risk assessment or analysis is carried out correctly, we have used the following few points to identify the risks:

1. Identification of risks.2. Decide who/what will be harmed and in what way. 3. Evaluation of the risks.4. Results findings should be recorded and then it should be implemented.5. Reviewing of the assessment and update accordingly.

So during the coding phasing and testing phase of the project following risks should have kept in mind and taken care of.

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6.1 Project Risk Assessment

Risk Risk Level

(L/M/H)

Likelihood of Event Mitigation Strategy

Program size M Not Likely. Careful designing of modules and similar coding.

Error H Very Likely. Proper testing is done by unit testing at the time of coding.

Slow L Likely. Ensure a decent system to run tests on and a good connection at the same time.

Power consumption L Likely It will be managed in the maintenance phase.

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7. LITERATURE REVIEW

Gross Domestic Product (GDP)

Gross Domestic Product can be defined as a quantitative measure of the values of every

final goods and features services that are produced in the specified time period usually

reffered to as quarterly or yearl. The estimates of GDP are most commonly used to

figure out the performance in terms of economy and living in terms of standard of a

given country so that we can make comparisons with countries .

It cannot be relatable as a measure which is complete in terms of estimating economic

activity. It merely accounts for the determinant output and the value which is added at

each stage of necessar production, it doesn’t involve the whole some of output aside the

whole production phase. It forcefully leaves out transactions such as business to

business in the beginning and median stages of production.

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Data Analysis

If we come in terms of defining data analysis, we can express it as a process which

involves doing an inspection, followed by cleaning, transforming to the desired

formations and finally modelling a set of data obtained from a trusted source which can

be a website or a github repository. The main objective of finding out meaningful

information, to suggest inferences and to give advices for decision making. Data

analysis is known to have varied facets and ability of approaches, encapsulating very

varied techniques which come under a diversity of names in different domains.

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Machine Learning

The fact that Machine Learning is a field which is part of Computer Science is known to

every novice out there. It is also known that the field of machine learning has evolved

from the studiosity of recognition of pattern and learning theory through computation in

the field of Artifical Intelligence. The field of machine learning goes thourgh a journey

that studies and constructs algorithms that can learn from data sources of varied origins

and make predictions. The algorithms considered for machine learning are known to

build models from the input dataset, enabling them to make data driven assumptions.

Approaches to machine learning are of various types, some of them are listed below:

Decision tree learning

Association rule learning

Artificial neural networks

Clustering

Bayesian networks

Reinforcement learning

Representation learning

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8. DISCUSSION AND CONCLUSION

In this project we have examined economic data to analyze the GDP and viusalize the

growth of the Indian Economy, from the year 1951 to the year 2012. The GDP has

grown at a linear manner. Even though GDP is not a very dependable key indicator to

analyze economy, yet we can easily visualize how the GDP has grown into the recent

times. Also we closely can examine which industries are contributing majorly to the

GDP.

After analysis, we have come to the conclusion that the problem in hand is a regression

problem, and we can apply necessary regression algortihms to find the outcome of the

project. Since the problem is a regression problem, we can easily determine the

regression line, this regression line proves the fact that the GDP has grown in a rather

linear fashion over the years.

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