├── banner.png
├── .github
└── workflows
│ └── greetings.yml
├── License
└── README.md
/banner.png:
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https://raw.githubusercontent.com/CSI-SFIT/CSI-SFIT-Contribution-Archive/HEAD/banner.png
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/.github/workflows/greetings.yml:
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1 | name: Greetings
2 |
3 | on: [pull_request, issues]
4 |
5 | jobs:
6 | greeting:
7 | runs-on: ubuntu-latest
8 | steps:
9 | - uses: actions/first-interaction@v1
10 | with:
11 | repo-token: ${{ secrets.GITHUB_TOKEN }}
12 | issue-message: 'Thank you for contributing to our project 💜'
13 | pr-message: 'Thank you for your contribution 💜'
14 |
--------------------------------------------------------------------------------
/License:
--------------------------------------------------------------------------------
1 | MIT License
2 |
3 | Copyright (c) 2020 CSI SFIT
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 |
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 |
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 |
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/README.md:
--------------------------------------------------------------------------------
1 | # ⚡ CSI SFIT Contribution Archive
2 |
3 | 
4 |
5 |
6 | CSI SFIT Contribution Archives
7 | A repository of all the links of technical articles, research papers & projects of our CSI SFIT Team members over the years.
8 |
9 |
10 | ## Table of Contents
11 | 1. Research Papers
12 | 2. Medium Articles
13 | 3. Projects
14 | ---
15 | ### 1. Research Papers
16 | ***List of all the research papers published by our CSI SFIT Team members over the years:***
17 |
18 | 1. [Automated Identification of Disaster News for Crisis Management using Machine Learning and Natural Language Processing](https://ieeexplore.ieee.org/document/9156031/authors#authors)
19 | Jul 4, 2020 | Institute of Electrical and Electronics Engineers (IEEE)
We are living in unprecedented times and anyone in this world could be impacted by natural disasters in some way or the other. Life is unpredictable and what is to come is unforeseeable. Nobody knows what the very next moment will hold, maybe it could be a disastrous one too. The past cannot be changed but it can act constructively towards the betterment of the current situation, ‘Precaution is better than cure’. To be above this uncertain dilemma of life and death situations, ‘Automated Identification of Disaster News for Crisis Management is proposed using Machine Learning and Natural Language Processing’. A software solution that can help disaster management websites to dynamically show the disaster relevant news which can be shared to other social media handles through their sites.
20 |
21 |
22 |
23 | Authors from CSI SFIT:
24 |
47 |
48 |
49 | 2. [A Comparative Study on Solar Power Forecasting using Ensemble Learning](https://ieeexplore.ieee.org/document/9142884/authors#authors)
50 | June 15, 2020 publication | Institute of Electrical and Electronics Engineers (IEEE)
51 | Intensifying requests for energy is preceding towards renewable solar energy integration with nonrenewable energy resources. Unlike other nonrenewable energy resources, solar energy is recurrent. Effectual utilization of spontaneously available energy accurate solar power forecasting is essential. This study aims to predict solar power through deep neural networks (DNNs) and various machine learning (ML) techniques on a solar dataset, namely linear regression, support vector regression, random forest, etc. The dataset that is used contains solar power energy extracted every five minutes. Moreover, a comparative study is carried out between DNNs and ML techniques, which helps in crafting suitable decisions to select appropriate forecasting and prediction techniques.
52 |
53 |
54 |
55 | Authors from CSI SFIT:
56 |
71 |
72 |
73 | 3. [Suspect Face Generation](https://ieeexplore.ieee.org/document/9137812/authors#authors)
74 | April 3, 2020 | Institute of Electrical and Electronics Engineers (IEEE)
75 | Currently sketch artists are employed by the police to draw sketches of suspects based on the description given by an eye-witness. These sketches can sometimes be inaccurate due to incorrect drawings of the artist or the incorrect description given by the witness. Generative Adversarial Network (GAN) is a way of training a Neural Network to output images which belong to a specific class. This network is trained by using an adversarial process which pits the generator against the discriminator in a minimax game. Traditional GANs are unable to generate high-resolution images hence, StyleGAN is used to resolve this issue. The generated images may still need to be altered to get a close match so TL-GAN is used to alter the generated image by altering the latent-space input of the StyleGAN. TL-GAN offers users the ability to finely tune one or multiple features of the face holistically. The main objective of the proposed work is to develop a Suspect Face Generation System as the sketches made by sketch artists are only 13 out of 160 times (approx. 8%) accurate. This system will help the society in reduction of misidentification of crime suspects and considerably reduce the crime rate.
76 |
77 |
78 |
79 | Authors from CSI SFIT:
80 |
93 |
94 |
95 | ---
96 | ### 2. Medium Articles
97 | ***List of all the Medium Articles published by our CSI SFIT Team members over the years:***
98 |
99 | 1. [The ideal workflow for your Machine Learning Project by Kaif Kohari](https://medium.com/@kaifkohari10/the-ideal-workflow-for-your-machine-learning-project-9df1a7125b17)
100 | **In this blog**, [@Kaif10](https://github.com/Kaif10) have **_summarized_** all the things one should be aware of while working on a Machine Learning project, from data cleaning and analysis **_to_** choosing the right model and hyperparameter tuning.
101 |
102 | 2. [The Large Hadron Collider with Machine Learning by Kaif Kohari](https://medium.com/@kaifkohari10/the-large-hadron-collider-with-machine-learning-7471024ad557)
103 | **In this blog**, [@Kaif10](https://github.com/Kaif10) have **_writes_** about the Introduction to the Large Hadron Collider, Basic Particle Physics, Working of Large Hadron Collider, Higgs Boson, Machine Learning, Results and Conclusion.
104 |
105 | 3. [Video-Game Sales Analysis with Python by Kaif Kohari](https://medium.com/@kaifkohari10/video-game-sales-analysis-with-python-68c60648820f)
106 | **In this blog**, [@Kaif10](https://github.com/Kaif10) **_works_** with a cool dataset which contains data about Video Games sales across various regions in the world from 2015.
107 |
108 | 4. [Conditional statements in Python by Jayashree Domala](https://medium.com/@domalajayashree/conditional-statements-in-python-f9819aa983b5)
109 | A guide to understanding if, else, elif statements in python.
110 |
111 | 5. [Python comparison operators by Jayashree Domala](https://medium.com/@domalajayashree/python-comparison-operators-a97780eb87ad)
112 | Guide to understand the working of comparison operators in Python.
113 |
114 | 6. [Python I/O commands for text files by Jayashree Domala](https://medium.com/@domalajayashree/python-i-o-commands-for-text-files-296f33502feb)
115 | An informative guide to perform I/O basics with text files.
116 |
117 | 7. [Booleans in Python by Jayashree Domala](https://medium.com/@domalajayashree/booleans-in-python-c11605d01ba1)
118 | A guide to understanding booleans in Python.
119 |
120 | 8. [Sets in Python by Jayashree Domala](https://medium.com/@domalajayashree/sets-in-python-b8a6aa6899d6)
121 | A guide to knowing more about set data type in Python.
122 |
123 | 9. [Tuples in python by Jayashree Domala](https://medium.com/@domalajayashree/tuples-in-python-6f3cf07ddfdc)
124 | A guide to understanding tuples in Python.
125 |
126 | 10. [Understanding python dictionaries by Jayashree Domala](https://medium.com/@domalajayashree/understanding-python-dictionaries-5639ed677d48)
127 | A guide to learn about dictionaries in Python.
128 |
129 | 11. [Understanding lists in Python by Jayashree Domala](https://medium.com/@domalajayashree/understanding-python-dictionaries-5639ed677d48)
130 | A guide to learn about dictionaries in Python.
131 |
132 | 12. [Geometry of linear equations for machine learning by Jayashree Domala](https://medium.com/@domalajayashree/geometry-of-linear-equations-for-machine-learning-3253577a77f6)
133 | A guide to help you understand linear algebra to get started with machine learning.
134 |
135 | 13. [Understanding Python strings by Jayashree Domala](https://medium.com/@domalajayashree/understanding-python-strings-8783506a9a4a)
136 | A guide to understand the python strings and string formatting.
137 |
138 | 14. [Understanding python number data type in detai by Jayashree Domalal](https://medium.com/@domalajayashree/understanding-python-number-data-type-in-detail-de061daefef8)
139 | A guide to help you understand the Python number data type.
140 |
141 | 15. [How to set up python in a Windows system? by Jayashree Domala](https://medium.com/@domalajayashree/how-to-set-up-python-in-a-windows-system-920d6ac2549b)
142 | A step by step guide for python installation.
143 |
144 | 16. [Understanding Artificial Intelligence and its subsets by Jayashree Domala](https://medium.com/@domalajayashree/understanding-artificial-intelligence-and-its-subsets-8e20a493d598)
145 | A guide to know about AI subsets and how to get started with it.
146 |
147 | 17. [Lyrics Generator using LSTM on TF 2.0 by Manmohan Dogra](https://medium.com/analytics-vidhya/lyrics-generator-using-lstm-on-tf-2-0-3baf524129b0)
148 | In this article, you will learn the essentials of RNN’s LSTM model, basic about NLP, and how to utilize them to make a Lyrics Generator on feeding few words as input by utilizing the Tensorflow 2.0 framework.
149 |
150 | 18. [How to visualize data using Power BI? by Jenny Dcruz](https://towardsdatascience.com/how-to-visualize-data-using-power-bi-9ec1413e976e)
151 | Use Microsoft Power BI to gain business intelligent insights.
152 |
153 | 19. [Excel, Tableau, Power BI… What should you use? by Jenny Dcruz](https://towardsdatascience.com/excel-tableau-power-bi-what-should-you-use-336ef7c8f2e0)
154 | Find out what you need for data analysis or visualization.
155 |
156 | 20. [Artificial Intelligence in Web Development by Jenny Dcruz](https://blog.usejournal.com/artificial-intelligence-in-web-development-ed1514f5cf2e)
157 | Learn how to take customer engagement to a new level.
158 |
159 | 21. [Fundamentals of NumPy by Jenny Dcruz](https://towardsdatascience.com/fundamentals-of-numpy-a7e94d260845)
160 | Over the course of this article, you will learn the various features and functions of the Python library, NumPy.
161 |
162 | 22. [Pandas for data analysis by Jenny Dcruz](https://towardsdatascience.com/pandas-for-data-analysis-142be71f63dc)
163 |
164 | 23. [Tableau visualizations by Jenny Dcruz](https://towardsdatascience.com/tableau-visualizations-dc9e544dc9a8)
165 |
166 | 24. [How to get financial data using Python? by Jayashree Domala](https://jayashree8.medium.com/how-to-get-financial-data-using-python-7a508f25fc39)
167 |
168 |
169 |
170 | Authors from CSI SFIT:
171 |
194 |
195 | ---
196 | ### 3. Projects
197 | ***List of all the projects done by our CSI SFIT Team members over the years:***
198 |
To be added.
199 |
200 | ---
201 | ### **How to Contribute:**
202 |
203 | 1. Clone repo and create a new branch: `$ git checkout https://github.com/CSI-SFIT/CSI-SFIT-Contribution-Archive.git -b name_for_new_branch`.
204 | 2. Make changes and test.
205 | 3. Submit Pull Request with comprehensive description of changes.
206 |
207 | **Acknowledgements**
208 | ---
209 |
210 | **CSI SFIT Team 2020 - 2021 :**
211 | + Chairperson : [@Delicia Fernandes](https://github.com/deliciafernandes)
212 |
213 |
214 |
215 | 
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