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Aakash K. on LinkedIn: #research #ai #productivity | 79 comments
Research papers are a valuable source of insights!!!
But finding the meaningful information takes hours.
Introducing Consensus: an AI-powered search engine⦠| 79 comments on LinkedIn
But finding the meaningful information takes hours.
Introducing Consensus: an AI-powered search engine⦠| 79 comments on LinkedIn
Best 80+ resources for Python Developers!
π Beginner Online Courses:
1. Codecademy: Learn Python 3
2. Coursera: Python for Everybody
3. edX: Introduction to Python: Absolute Beginner
4. Udemy: Complete Python Bootcamp
5. Khan Academy: Intro to Python Programming
π Intermediate Online Courses:
1. Coursera: Python Data Structures
2. edX: Intermediate Python
3. Udacity: Introduction to Computer Science
4. Pluralsight: Python Fundamentals
5. Linkedln Learning: Intermediate Python
π Advanced Online Courses:
1. Coursera: Applied Data Science with Python
2. edX: Advanced Python for Data Science
3. Udemy: Python for Data Science and Machine Learning Bootcamp
4. MIT OpenCourseWare: Introduction to Computer Science and Programming in Python
5. DataCamp: Python for Statistical Analysis
π Practice:
1. HackerRank: Python Practice
2. LeetCode: Python Problems
3. Exercism: Python Exercises
4. CodingBat: Python Practice
5. Codewars: Python Challenges
π Project-Based Learning:
1. Real Python: Python Developer's Guide
2. PythonProjects.dev: Python Project Ideas with Tutorials
3. PyBites: 100 Days of Code Challenges
4. Kaggle: Python Data Science Notebooks
5. JetBrains Academy: Python Track (Project-Based Learning)
π YouTube Channels:
1. Corey Schafer: Python Tutorials
2. Sentdex: Python Programming Tutorials
3. Tech With Tim: Python Programming
4. CS Dojo: Python Programming for Beginners
5. Telusko: Python Programming Tutorials
π Documentation:
1. Python Official Documentation
2. Python Standard Library Documentation
π Beginner Books:
1. "Python Crash Course" by Eric Matthes
2. "Automate the Boring Stuff with Python" by Al Sweigart
3. "Learn Python 3 the Hard Way" by Zed A. Shaw
4. "Python for Kids" by Jason R. Briggs
5. "Python Playground" by Mahesh Venkitachalam
π Intermediate/Advanced Books:
1. "Fluent Python" by Luciano Ramalho
2. "Python Cookbook" by David Beazley and Brian K. Jones
3. "Effective Python" by Brett Slatkin
4. "Learning Python" by Mark Lutz
5. "Python Design Patterns" by Chetan Giridhar
π Blogs and Websites:
1. Real Python
2. [Python.org](http://python.orgas Blog
3. Towards Data Science (Python Section)
4. Full Stack Python
5. Python Insider (Official Python Blog)
π Important Libraries:
1. NumPy
2. Pandas
3. Matplotlib
4. Seaborn
5. Scikit-learn
π Tools and Environments:
1. Jupyter Notebook / JupyterLab
2. PyCharm
3. Visual Studio Code (VS Code)
4. Anaconda
5. Virtualenv / Conda
π Data Analysis and Manipulation:
1. Openpyxl
2. Beautiful Soup
3. Requests
4. SQLAIchemy
5. NLTK (Natural Language Toolkit)
π Web Development:
1. Django
2. Flask
3. FastAPl
4. Beautiful Soup
5. Requests
π Machine Learning and Data Science:
1. TensorFlow
2. PyTorch
3. Keras
4. XGBoost
5. Statsmodels
π Beginner Online Courses:
1. Codecademy: Learn Python 3
2. Coursera: Python for Everybody
3. edX: Introduction to Python: Absolute Beginner
4. Udemy: Complete Python Bootcamp
5. Khan Academy: Intro to Python Programming
π Intermediate Online Courses:
1. Coursera: Python Data Structures
2. edX: Intermediate Python
3. Udacity: Introduction to Computer Science
4. Pluralsight: Python Fundamentals
5. Linkedln Learning: Intermediate Python
π Advanced Online Courses:
1. Coursera: Applied Data Science with Python
2. edX: Advanced Python for Data Science
3. Udemy: Python for Data Science and Machine Learning Bootcamp
4. MIT OpenCourseWare: Introduction to Computer Science and Programming in Python
5. DataCamp: Python for Statistical Analysis
π Practice:
1. HackerRank: Python Practice
2. LeetCode: Python Problems
3. Exercism: Python Exercises
4. CodingBat: Python Practice
5. Codewars: Python Challenges
π Project-Based Learning:
1. Real Python: Python Developer's Guide
2. PythonProjects.dev: Python Project Ideas with Tutorials
3. PyBites: 100 Days of Code Challenges
4. Kaggle: Python Data Science Notebooks
5. JetBrains Academy: Python Track (Project-Based Learning)
π YouTube Channels:
1. Corey Schafer: Python Tutorials
2. Sentdex: Python Programming Tutorials
3. Tech With Tim: Python Programming
4. CS Dojo: Python Programming for Beginners
5. Telusko: Python Programming Tutorials
π Documentation:
1. Python Official Documentation
2. Python Standard Library Documentation
π Beginner Books:
1. "Python Crash Course" by Eric Matthes
2. "Automate the Boring Stuff with Python" by Al Sweigart
3. "Learn Python 3 the Hard Way" by Zed A. Shaw
4. "Python for Kids" by Jason R. Briggs
5. "Python Playground" by Mahesh Venkitachalam
π Intermediate/Advanced Books:
1. "Fluent Python" by Luciano Ramalho
2. "Python Cookbook" by David Beazley and Brian K. Jones
3. "Effective Python" by Brett Slatkin
4. "Learning Python" by Mark Lutz
5. "Python Design Patterns" by Chetan Giridhar
π Blogs and Websites:
1. Real Python
2. [Python.org](http://python.orgas Blog
3. Towards Data Science (Python Section)
4. Full Stack Python
5. Python Insider (Official Python Blog)
π Important Libraries:
1. NumPy
2. Pandas
3. Matplotlib
4. Seaborn
5. Scikit-learn
π Tools and Environments:
1. Jupyter Notebook / JupyterLab
2. PyCharm
3. Visual Studio Code (VS Code)
4. Anaconda
5. Virtualenv / Conda
π Data Analysis and Manipulation:
1. Openpyxl
2. Beautiful Soup
3. Requests
4. SQLAIchemy
5. NLTK (Natural Language Toolkit)
π Web Development:
1. Django
2. Flask
3. FastAPl
4. Beautiful Soup
5. Requests
π Machine Learning and Data Science:
1. TensorFlow
2. PyTorch
3. Keras
4. XGBoost
5. Statsmodels
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How to Make Money with ChatGPT in 2023 | Aakash K. posted on the topic | LinkedIn
How to Make Money with ChatGPT in 2023 ?
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ChatGPT is an endless idea machine. You can use it to generate⦠| 28 comments on LinkedIn
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ChatGPT is an endless idea machine. You can use it to generate⦠| 28 comments on LinkedIn