📚 Table of Contents

🔰 ABOUT

Below are the topics you'll find in this repository:

🔹 Python

🔹 Statistics

🔹 Machine learning

🔹 Deep learning

🔹 Computer vision

🔹 Natural language processing

🔹 Big Data

🔹 Apache Spark

🔹 Apache Kafka

🔹 Data Analytics

🔹 PowerBI

🔹 Tableau

🔹 Databases

🔹 Data Science Workflow

🔹 Real Time Data Science Projects

To get started, you'll need to have Python installed on your computer. You can download the latest version of Python from the official website: https://www.python.org/downloads/
You'll also need to have Jupyter installed. You can install it using pip using below commands :

pip install jupyter

Once you have Python and Jupyter installed, you can clone this repository:

git clone https://github.com/creativepuru/Python-Basics.git

Then, navigate to the directory where the repository was cloned and start Jupyter by using below commands :

cd <Python-Basics>
jupyter notebook

This will open the Jupyter notebook interface in your default web browser. From here, you can navigate to the notebooks directory and open any of the notebooks to view the code examples.

👋 Welcome to the PWSKILLS Assignments Repository!
📚 This repository contains a collection of assignments related to Python, Data Science, Machine Learning, and Artificial Intelligence, curated by the team at PWSKILLS.
🚀 Our goal is to provide a comprehensive resource for those looking to improve their skills in these exciting fields. Whether you're a beginner or an expert, you'll find plenty of challenges and opportunities to learn and grow.
💻 Each assignment is accompanied by a set of instructions and sample code, designed to guide you through the task and help you develop your skills. We encourage you to experiment with the code and try out your own ideas.
📈 As you progress through the assignments, you'll build a solid foundation in Python and gain experience in using popular data science libraries such as NumPy, Pandas, and Matplotlib. You'll also explore cutting-edge topics like machine learning and artificial intelligence, learning how to build predictive models and intelligent agents.

🙌 We value your feedback and opinions. If you have any comments, suggestions, or feedback about our assignments, please share them with us in this section.
💬 To provide feedback, you can open a new issue under Issues tab and describe your thoughts. We welcome any feedback that can help us improve the quality of our assignments, including code examples, new topics or problems, typos or errors, or any other suggestions.
👨‍💻 We are constantly striving to improve our assignments and make them more useful and accessible for our users. Your feedback can help us achieve that goal.
🤝 We appreciate your support and look forward to hearing from you.