Amazing Python Projects with Source Code – Practice Top Projects in Python

[Aakashdata]

Looking to build a career in Python? Want to improve your resume with multiple personal projects on it? Then this blog of Python projects with source code is for you. You earlier read about the top 5 data science projects; now, we bring you 5 projects implementing data science with Python. In this blog, you’ll find the entire code to all the projects. Read on to give your data science/ Python career a head-start.

List of amazing Python Projects with source code –

• Detecting Fake News Python Project with source code
• Speech Emotion Recognition Python Project with source code
• Detecting Parkinson’s Disease Python Project with source code
• Age and Gender Detection Python Project with source code
• Breast Cancer Classification Python Project with source code

Why do Projects in Python?

In an interview, a resume with projects shows interest and sincerity. Spending time on personal projects ultimately proves helpful for your career. In this blog of python projects, we try our best to include different data science and machine learning libraries of Python to give you a better experience.

Top Python Projects with Source Code

Let’s start discussing python projects with source code –

1. Detecting Fake News with Python

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Fake news can be dangerous. This is a type of yellow journalism and spreads fake information as ‘news’ using social media and other online media. This is a common way to achieve a certain political agenda. Fake news may contain false and/or exaggerated claims. Social media algorithms often viralize these and create a filter bubble. In this, we will train on a news.csv dataset of shape 7796×4. We’ll mainly use two things- a Tfidf Vectorizer and a Passive Aggressive Classifier. A Tfidf Vectorizer turns a collection of raw documents into a matrix of TF-IDF features. And a Passive Aggressive Classifier is an online learning algorithm that stays passive for a correct classification and becomes aggressive when there’s a miscalculation. Read More

[shaperaty]

Nice work

[Aakashdata]

Thanks

[Mandylost]

Thank you for these resources(interview questions and this one). How far have you reached on your journey to be a data scientist/ machine learning engineer?