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COVID Vaccination Data Analysis

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  COVID-19 Vaccination Data Analysis The Covid-19 pandemic is the most critical health disaster to hit the world. Predicting the trend of COVID-19 vaccination has become a challenge. Many healthcare professionals, statisticians, and researchers are tracking the spread of the virus in different parts of the world using a variety of approaches. The increase in a variety of vaccines developed by talented scientists and the vaccination process sparked curiosity to learn more about current immunization programs and a keen interest in finding meaningful information from the data. After looking up multiple websites, I found a few datasets to work with.  The complete code is available on  GitHub  along with the dataset . Data Collection First, we will import libraries and the dataset. The dataset we’ll use for this project- we’ll call it cowin-2.csv . Required packages:(pandas ,matplotlib,seaborn)           import  pandas  as  pd           import  matplotlib.pyplot  as  plt           import
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Fake News Detection Project (ML)

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Fake News Detection  Fake news simply means - to incorporate information that leads people to the wrong path. Nowadays fake news is spreading a lot and people share this information without verifying it.  Fake news detection is a severe yet challenging problem. The rapid rise of social networking platforms has not only yielded an enormous increase in information but has also stimulated the spread of fake news. Thus, the effect of fake news has been increasing, sometimes extending to the offline world and intimidating public safety. Given a large amount of web content, automatic fake news detection is a practical solution useful to all online content providers, to reduce the human time and effort to detect and prevent the spread of fake news.  Detecting Fake News using Python First, we will import libraries and the dataset. The dataset we’ll use for this project- we’ll call it news.csv which has a shape of 7796×4 (7796 rows and 4 columns). Required packages: pip install pandas pip insta
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ML Internship at Dlithe

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Internship at DLithe Being agile is the need of the hour. The world is in disruptive mode. It is looking for an agile workforce that is adaptable and produces quicker results. While academics and work provide required knowledge and experience, but individuals must bridge gaps in skills. In this digital world, DLithe is what helps you upgrade your skills and be competent to work in the agile world. Internship Journey The course started from the basics of the python programming language and then went on to machine learning which involved interesting projects like a chatbot, iris flower species identification,  message encryption-decryption, real estate price prediction, and many other real-life projects. We received a series of assignments every week that incrementally solved a real-world machine learning problem. Python Programming   The first few days of the internship were completely devoted to learning the basics of python which included topics like variables, operators
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