The document is a presentation on fake news detection. It discusses what fake news detection is, how to identify fake news through both manual and automated methods, and the machine learning approaches used in automated detection. It describes the tools and technologies used to develop their fake news detection platform, including Python programming language, NumPy, Pandas, Matplotlib, Seaborn, and Scikit-learn libraries. Their platform was developed using Jupyter Notebook for its interactive and shareable environment. The presentation concludes with demonstrating how their platform works and its high accuracy rate.
Fake news has a negative impact on individuals and society, hence the detection of fake news is becoming a bigger field of interest for data scientists. Attempts to leverage artificial intelligence technologies particularly machine/deep learning techniques and natural language processing (NLP) to automatically detect fake news and prevent its viral spread have recently been actively discussed.
Large technology companies have begun to take steps to address this trend. For example, Google has adjusted its news rankings to prioritize well-known sites and has banned sites with a history of spreading fake news. Facebook has integrated fact checking organizations into its platform.
This SlideShare explores the concept of NLP for detecting fake news in brief.
Recently, fake news has been incurring many problems to our society. As a result, many researchers have been working on identifying fake news. Most of the fake news detection systems utilize the linguistic feature of the news. However, they have difficulty in sensing highly ambiguous fake news which can be detected only after identifying meaning and latest related information. In this paper, to resolve this problem, we shall present a new Korean fake news detection system using fact DB which is built and updated by human's direct judgement after collecting obvious facts. Our system receives a proposition, and search the semantically related articles from Fact DB in order to verify whether the given proposition is true or not by comparing the proposition with the related articles in fact DB. To achieve this, we utilize a deep learning model, Bidirectional Multi Perspective Matching for Natural Language Sentence BiMPM , which has demonstrated a good performance for the sentence matching task. However, BiMPM has some limitations in that the longer the length of the input sentence is, the lower its performance is, and it has difficulty in making an accurate judgement when an unlearned word or relation between words appear. In order to overcome the limitations, we shall propose a new matching technique which exploits article abstraction as well as entity matching set in addition to BiMPM. In our experiment, we shall show that our system improves the whole performance for fake news detection. Prasanth. K | Praveen. N | Vijay. S | Auxilia Osvin Nancy. V ""Fake News Detection using Machine Learning"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30014.pdf
Paper Url : https://www.ijtsrd.com/engineering/information-technology/30014/fake-news-detection-using-machine-learning/prasanth-k
Fake news has a negative impact on individuals and society, hence the detection of fake news is becoming a bigger field of interest for data scientists. Attempts to leverage artificial intelligence technologies particularly machine/deep learning techniques and natural language processing (NLP) to automatically detect fake news and prevent its viral spread have recently been actively discussed.
Large technology companies have begun to take steps to address this trend. For example, Google has adjusted its news rankings to prioritize well-known sites and has banned sites with a history of spreading fake news. Facebook has integrated fact checking organizations into its platform.
This SlideShare explores the concept of NLP for detecting fake news in brief.
Recently, fake news has been incurring many problems to our society. As a result, many researchers have been working on identifying fake news. Most of the fake news detection systems utilize the linguistic feature of the news. However, they have difficulty in sensing highly ambiguous fake news which can be detected only after identifying meaning and latest related information. In this paper, to resolve this problem, we shall present a new Korean fake news detection system using fact DB which is built and updated by human's direct judgement after collecting obvious facts. Our system receives a proposition, and search the semantically related articles from Fact DB in order to verify whether the given proposition is true or not by comparing the proposition with the related articles in fact DB. To achieve this, we utilize a deep learning model, Bidirectional Multi Perspective Matching for Natural Language Sentence BiMPM , which has demonstrated a good performance for the sentence matching task. However, BiMPM has some limitations in that the longer the length of the input sentence is, the lower its performance is, and it has difficulty in making an accurate judgement when an unlearned word or relation between words appear. In order to overcome the limitations, we shall propose a new matching technique which exploits article abstraction as well as entity matching set in addition to BiMPM. In our experiment, we shall show that our system improves the whole performance for fake news detection. Prasanth. K | Praveen. N | Vijay. S | Auxilia Osvin Nancy. V ""Fake News Detection using Machine Learning"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30014.pdf
Paper Url : https://www.ijtsrd.com/engineering/information-technology/30014/fake-news-detection-using-machine-learning/prasanth-k
DETECTION OF FAKE ACCOUNTS IN INSTAGRAM USING MACHINE LEARNINGijcsit
With the advent of the Internet and social media, while hundreds of people have benefitted from the vast sources of information available, there has been an enormous increase in the rise of cyber-crimes, particularly targeted towards women. According to a 2019 report in the [4] Economics Times, India has witnessed a 457% rise in cybercrime in the five year span between 2011 and 2016. Most speculate that this is due to impact of social media such as Facebook, Instagram and Twitter on our daily lives. While these definitely help in creating a sound social network, creation of user accounts in these sites usually needs just an email-id. A real life person can create multiple fake IDs and hence impostors can easily be made. Unlike the real world scenario where multiple rules and regulations are imposed to identify oneself in a unique manner (for example while issuing one’s passport or driver’s license), in the virtual world of social media, admission does not require any such checks. In this paper, we study the different accounts of Instagram, in particular and try to assess an account as fake or real using Machine Learning techniques namely Logistic Regression and Random Forest Algorithm.
Make a query regarding a topic of interest and come to know the sentiment for the day in pie-chart or for the week in form of line-chart for the tweets gathered from twitter.com
20 Latest Computer Science Seminar Topics on Emerging TechnologiesSeminar Links
A list of Top 20 technical seminar topics for computer science engineering (CSE) you should choose for seminars and presentations in 2019. The list also contains related seminar topics on the emerging technologies in computer science, IT, Networking, software branch. To download PDF, PPT Seminar Reports check the links.
"The proposed system overcomes the above mentioned issue in an efficient way. It aims at analyzing the number of fraud transactions that are present in the dataset.
"
This is the idea which we submitted as part of Smart India Hackathon 2019. The problem statement asked to create a platform to display the various projects created by the students all across India.
Our Team:
Abhishek Varghese ( Team Lead )
Gaurav Ganna ( Me )
Shivan Kumar
Himali Goel
Manika Khare
Raj Hansini Khoiwal
Cyber Security.
Watch my videos on snack here: --> --> http://sck.io/x-B1f0Iy
@ Kindly Follow my Instagram Page to discuss about your mental health problems-
-----> https://instagram.com/mentality_streak?utm_medium=copy_link
@ Appreciate my work:
-----> behance.net/burhanahmed1
Thank-you !
Twitter Sentiment Analysis Project Done using R.
In these Project we deal with the tweets database that are avaialble to us by the Twitter. We clean the tweets and break them out into tokens and than analysis each word using Bag of Word concept and than rate each word on the basis of the score wheter it is positive, negative and neutral.
We used Naive Baye's Classifier as our base.
Artificial Intelligence with Python | EdurekaEdureka!
YouTube Link: https://youtu.be/7O60HOZRLng
* Machine Learning Engineer Masters Program: https://www.edureka.co/masters-program/machine-learning-engineer-training *
This Edureka PPT on "Artificial Intelligence With Python" will provide you with a comprehensive and detailed knowledge of Artificial Intelligence concepts with hands-on examples.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Building a multi headed model thats capable of detecting different types of toxicity like threats, obscenity, insult and identity based hate. Discussing things you care about can be difficult. The threat of abuse and harassment online means that many people stop expressing themselves and give up on seeking different opinions. Platforms struggle to efficiently facilitate conversations, leading many communities to limit or completely shut down user comments. So far we have a range of publicly available models served through the perspective APIs, including toxicity. But the current models still make errors, and they dont allow users to select which type of toxicity theyre interested in finding. Pallam Ravi | Hari Narayana Batta | Greeshma S | Shaik Yaseen ""Toxic Comment Classification"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23464.pdf
Paper URL: https://www.ijtsrd.com/computer-science/other/23464/toxic-comment-classification/pallam-ravi
DETECTION OF FAKE ACCOUNTS IN INSTAGRAM USING MACHINE LEARNINGijcsit
With the advent of the Internet and social media, while hundreds of people have benefitted from the vast sources of information available, there has been an enormous increase in the rise of cyber-crimes, particularly targeted towards women. According to a 2019 report in the [4] Economics Times, India has witnessed a 457% rise in cybercrime in the five year span between 2011 and 2016. Most speculate that this is due to impact of social media such as Facebook, Instagram and Twitter on our daily lives. While these definitely help in creating a sound social network, creation of user accounts in these sites usually needs just an email-id. A real life person can create multiple fake IDs and hence impostors can easily be made. Unlike the real world scenario where multiple rules and regulations are imposed to identify oneself in a unique manner (for example while issuing one’s passport or driver’s license), in the virtual world of social media, admission does not require any such checks. In this paper, we study the different accounts of Instagram, in particular and try to assess an account as fake or real using Machine Learning techniques namely Logistic Regression and Random Forest Algorithm.
Make a query regarding a topic of interest and come to know the sentiment for the day in pie-chart or for the week in form of line-chart for the tweets gathered from twitter.com
20 Latest Computer Science Seminar Topics on Emerging TechnologiesSeminar Links
A list of Top 20 technical seminar topics for computer science engineering (CSE) you should choose for seminars and presentations in 2019. The list also contains related seminar topics on the emerging technologies in computer science, IT, Networking, software branch. To download PDF, PPT Seminar Reports check the links.
"The proposed system overcomes the above mentioned issue in an efficient way. It aims at analyzing the number of fraud transactions that are present in the dataset.
"
This is the idea which we submitted as part of Smart India Hackathon 2019. The problem statement asked to create a platform to display the various projects created by the students all across India.
Our Team:
Abhishek Varghese ( Team Lead )
Gaurav Ganna ( Me )
Shivan Kumar
Himali Goel
Manika Khare
Raj Hansini Khoiwal
Cyber Security.
Watch my videos on snack here: --> --> http://sck.io/x-B1f0Iy
@ Kindly Follow my Instagram Page to discuss about your mental health problems-
-----> https://instagram.com/mentality_streak?utm_medium=copy_link
@ Appreciate my work:
-----> behance.net/burhanahmed1
Thank-you !
Twitter Sentiment Analysis Project Done using R.
In these Project we deal with the tweets database that are avaialble to us by the Twitter. We clean the tweets and break them out into tokens and than analysis each word using Bag of Word concept and than rate each word on the basis of the score wheter it is positive, negative and neutral.
We used Naive Baye's Classifier as our base.
Artificial Intelligence with Python | EdurekaEdureka!
YouTube Link: https://youtu.be/7O60HOZRLng
* Machine Learning Engineer Masters Program: https://www.edureka.co/masters-program/machine-learning-engineer-training *
This Edureka PPT on "Artificial Intelligence With Python" will provide you with a comprehensive and detailed knowledge of Artificial Intelligence concepts with hands-on examples.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Building a multi headed model thats capable of detecting different types of toxicity like threats, obscenity, insult and identity based hate. Discussing things you care about can be difficult. The threat of abuse and harassment online means that many people stop expressing themselves and give up on seeking different opinions. Platforms struggle to efficiently facilitate conversations, leading many communities to limit or completely shut down user comments. So far we have a range of publicly available models served through the perspective APIs, including toxicity. But the current models still make errors, and they dont allow users to select which type of toxicity theyre interested in finding. Pallam Ravi | Hari Narayana Batta | Greeshma S | Shaik Yaseen ""Toxic Comment Classification"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23464.pdf
Paper URL: https://www.ijtsrd.com/computer-science/other/23464/toxic-comment-classification/pallam-ravi
Top 5 Machine Learning Tools for Software Development in 2024.pdfPolyxer Systems
Machine learning has been widely used by various industries in 2023. The software development industry can take great advantage of machine learning in 2024 as well.
It has great potential to revolutionize various aspects of software development including task automation, boosting user experience, and easy software development and deployment.
Artificial Intelligence: Survey of Cybersecurity Capabilities, Ethical Concer...Petar Radanliev
The comprehensive survey articulates the multifaceted dimensions of Artificial Intelligence (AI), spanning its historical roots, advancements, and ethical dilemmas. It starts by tracing the intellectual lineage of AI to ancient mythology and proceeds to discuss the revolutionary contributions of Generative Pre-trained Transformers (GPT), particularly GPT-4, in problem-solving and real-world applications. The paper also delves into the darker applications of AI, including its role in cyberattacks and automated phishing. Various techniques of adversarial attacks that undermine AI systems, such as Fast Gradient Sign Method (FGSM), Jacobian-based Saliency Map Attack (JSMA), and Universal Adversarial Perturbations (UAP), are meticulously examined. The paper further expounds on Membership Inference Attacks (MIA), a significant privacy concern, and presents various strategies to defend against adversarial attacks. A global perspective on AI regulations, encompassing UK, New Zealand, the EU, and China policies, is also provided. It culminates in weighing the ethical considerations against the security risks in AI, contextualised by global crime statistics. This survey serves as an exhaustive resource for understanding AI's complexity, capabilities, and ethical implications, offering invaluable insights for researchers, policymakers, and industry experts.
We are seeing an explosion of the use of Bots in the areas of sales and customer service, but what makes a Chatbot useful? During the recent rise in Chatbot popularity we have seen many bad deployments, so how can you avoid the pitfalls and ensure your Bot succeeds?
Join us to learn all about the new world of Chatbots, Artificial Intelligence, Neuro-linguistic programming, Machine Learning and best practices for deploying the technology for your business.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
In this webinar, experts Kyle Barkins and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply AI to help improve your nonprofit's website experience, social media, content and more.
As an entrepreneur or small business owner, have you ever dreamed of marrying an accountant just so they can do the bookkeeping while you focus on growing your business? Instead, consider how a stack of mobile or desktop technology applications (apps) can help you spend less time on all those tasks small business owners have to manage.
Python Language is a multipurpose, high-level, object-oriented programming language , easy to learn. Python is a popular programming language used for developing applications and web services. Python's strong support of modules, subroutines and functions help in faster development of applications.
Learn Data Science with Python course for B.TECH, BCA, MCA, BSC, MSC, B.COM, and statistical students. Data Science with python online training course with certified industry experts. Get a 100 % pre-placement guarantee.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/09/responsible-ai-tools-and-frameworks-for-developing-ai-solutions-a-presentation-from-intel/
Mrinal Karvir, Senior Cloud Software Engineering Manager at Intel, presents the “Responsible AI: Tools and Frameworks for Developing AI Solutions” tutorial at the May 2023 Embedded Vision Summit.
Over 90% of businesses using AI say trustworthy and explainable AI is critical to business, according to Morning Consult’s IBM Global AI Adoption Index 2021. If not designed with responsible considerations of fairness, transparency, preserving privacy, safety and security, AI systems can cause significant harm to people and society and result in financial and reputational damage for companies.
How can we take a human-centric approach to design AI solutions? How can we identify different types of bias and what tools can we use to mitigate those? What are model cards, and how can we use them to improve transparency? What tools can we use to preserve privacy and improve security? In this talk, Karvir discusses practical approaches to adoption of responsible AI principles. She highlights relevant tools and frameworks and explores industry case studies. She also discusses building a well-defined response plan to help address an AI incident efficiently.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
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Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Planning Of Procurement o different goods and services
final presentation fake news detection.pptx
1. PRESENTATION ON
Under the Guidance of
Mr. Abhinav Gupta, Mr. Ravish Kumar Dubey & Ms. Jayati Bhardwaj
⚫⚫⚫
2. ⚫What is Fake News Detection?
Presentation
Outline
⚫How we can identify Fake News?
⚫How our platform/tool look like?
⚫Which language did we use to develop our platform?
⚫Which Libraries we've used?
⚫Which compiler/ Environment we've used and why?
⚫How our Fake News Detection works?
⚫Fact
TOPICS WE COVER
⚫C4 Group Present | Fake News Detection⚫
3. Fake News Detection is a tool or platform that detect information
content that is false, misleading or whose source cannot be verified.
This content may be generated to intentionally damage reputations,
deceive, or to gain attention.
What is
Fake News
Detection?
Misinformation presents a huge challenge in online society. As a result,
there have been many attempts to identify and classify misinformation.
Specifically, in social networking sites, blogs, as well as online
newspapers.
⊱⚫⊱
⚫C4 Group Present | Fake News Detection⚫
4. There are two methods to identify Fake News:
1. Manual Fake News Detection
2. Automated Fake News Detection
How we can
identify Fake
News?
Manual Fake News Detection: Manual fake news detection often
involves all the techniques and procedures a person can use to
verify the news. But, the amount of data generated online daily
is overwhelming.
Automated Fake News Detection: Automated detection systems
provide value in terms of automation and scalability. There are
various techniques and approaches implemented in fake news
detection research.
⊱⚫⊱
⚫C4 Group Present | Fake News Detection⚫
5. There is also many approaches in Automated Fake News Detection:
Machine Learning approach: Machine Learning refers to giving
computers the ability to learn without explicitly being
How we can
identify Fake
News?
programmed. A machine learning approach uses machine
learning algorithms to detect misinformation.
Example:
Logistic Regression
Decision Tree
Gradient Boosting
Random Forest
⊱⚫⊱
⚫C4 Group Present | Fake News Detection⚫
7. Python is a general-purpose programming language, meaning it can be
used in the development of both web and desktop applications. It’s also
useful in the development of complex numeric and scientific applications.
With this sort of versatility, it comes as no surprise that Python is one of
the fastest-growing programming languages in the world.
Which language
did we use to
develop our
platform?
WHY IS PYTHON ESSENTIAL FOR DATA SCIENCE?
It’s Flexible
It’s Easy to Learn
It’s Open Source
It’s Well-Supported
⚫C4 Group Present | Fake News Detection⚫
8. NumPy: NumPy, which stands for Numerical Python, is a library
consisting of multidimensional array objects and a collection of
routines for processing those arrays.
Pandas: Pandas is an open-source, BSD-licensed Python library
providing high-performance, easy-to-use data structures and data
analysis tools for the Python programming language.
Matplotlib: Matplotlib is one of the most popular Python packages used
for data visualization.
Which libraries
we've used?
Seaborn: Seaborn is a library mostly used for statistical plotting in
Python.
NumPy
Pandas
Matplotlib
Seaborn
Sklearn
Sklearn: Scikit-learn (Sklearn) is the most useful and robust library for
machine learning in Python. It provides a selection of efficient tools for
machine learning and statistical modeling including classification,
regression, clustering and dimensionality reduction via a consistence
interface in Python.
⚫C4 Group Present | Fake News Detection⚫
9. Which compiler/
Environment we've used and
why?
JUPYTER NOTEBOOK
(OPEN SOURCE WEB BASED INTERACTIVE ENVIRONMENT)
The Jupyter Notebook is an open-source web application that allows you to create and share
documents that contain live code, equations, visualizations and narrative text. Uses include:
data cleaning and transformation, numerical simulation, statistical modeling, data
visualization, machine learning, and much more.
Advantages:
All in one place
Easy to share
Language independent
Interactive code
⚫C4 Group Present | Fake News Detection⚫
10. Steps to Use our Platform:
STEP: STEP:
Enter the news you want to check Now wait for a minute to pridict your
wheather is it Real or Fake? news.
STEP: STEP:
Tap on Run Button. Result.
⚫C4 Group Present | Fake News Detection⚫
12. HERE'S A FACT
8 OUT OF 10
USER USE OUR PLATFORM.
Because No Other Platform Gives You 90% Accuracy That The News You Want To
Predict That News Is Real Or Fake.
Fake news research has never been more important than it is now. Especially
during a time when the world is fighting a pandemic.
⚫C4 Group Present | Fake News Detection⚫
13. Thank You!
BY C4 GROUP MEMBERS:
⚫C4 Group Present | Fake News Detection⚫
