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materials reviews and mentions
- How to manage procrastination and lack of focus during learning?
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Other programing options?
Real Python (https://realpython.com/)
- Whats the best way to learn python for free?
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Best free sites to learn Python Courses
https://realpython.com are very good in my opinion.
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Recommended learning resources for rust
I know the official sites/books but am looking for something a bit more convenient and guided, similar to https://realpython.com/ which has really good text articles and also video courses covering specific topics.
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How do I get started with ML?
Learn Python: Python is the most popular language for ML and AI projects. Start by learning the basics of Python, then move on to more advanced topics. Some great resources for learning Python include: Codecademy's Python course: https://www.codecademy.com/learn/learn-python Real Python: https://realpython.com/ Mathematics: A solid understanding of mathematics, particularly linear algebra, calculus, probability, and statistics, is essential for ML. Here are some resources to help you learn: Khan Academy courses: Linear Algebra: https://www.khanacademy.org/math/linear-algebra Calculus: https://www.khanacademy.org/math/calculus-1 Probability and Statistics: https://www.khanacademy.org/math/statistics-probability 3Blue1Brown's YouTube series on Linear Algebra: https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab Data processing and manipulation: Familiarize yourself with popular Python libraries for data manipulation and analysis, such as NumPy, pandas, and matplotlib: NumPy: https://numpy.org/doc/stable/user/quickstart.html pandas: https://pandas.pydata.org/pandas-docs/stable/getting_started/intro_tutorials/index.html matplotlib: https://matplotlib.org/stable/tutorials/index.html Machine learning concepts: Learn about the basic concepts of ML, including supervised learning, unsupervised learning, and reinforcement learning. Some great resources include: Coursera's Machine Learning course by Andrew Ng: https://www.coursera.org/learn/machine-learning Google's Machine Learning Crash Course: https://developers.google.com/machine-learning/crash-course Fast.ai's Practical Deep Learning for Coders course: https://course.fast.ai/ Deep learning libraries: Get familiar with popular deep learning libraries such as TensorFlow and PyTorch: TensorFlow: https://www.tensorflow.org/tutorials PyTorch: https://pytorch.org/tutorials/ Specialize and work on projects: Choose an area of interest (such as natural language processing, computer vision, or reinforcement learning), and start working on projects to apply your skills. You can find datasets and project ideas from sources like: Kaggle: https://www.kaggle.com/ Papers With Code: https://paperswithcode.com/ Stay up-to-date and join the community: Follow ML blogs, podcasts, and conferences to stay current with the latest developments. Join ML communities and forums like r/MachineLearning on Reddit, AI Stack Exchange, or specialized Discord and Slack groups.
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FLOSSing for Lent 12/40 - Python
Real Python - A great place to learn python
- Donde aprender Python POSTA?
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Best websites to give me tasks?
There's many popular Python educational blogs out there. You can check out RealPython, PythonAlgos, LearnPython, and many more.
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GitHub - antedoro/arberia: Arberia Theme is a fully responsive tech-blogger theme for Hugo with 4 single post layout!
Question - Was this theme created by/for realpython.com and they've decided to open source it?
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A note from our sponsor - SonarLint
www.sonarlint.org | 8 Jun 2023
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realpython/materials is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of materials is HTML.