Welcome to my Machine Learning Learning Journey repository! This repository serves as a platform for documenting my day-wise revision and learning process of Machine Learning concepts, starting from the basics and progressing towards advanced topics.
In this repository, you will find my day-wise notes, code implementations, and projects as I explore the fascinating realm of Machine Learning. I will be sharing my progress, insights, and learnings each day to provide a comprehensive and transparent view of my learning journey. While I am not an expert in this field, I hope that sharing my journey will inspire and assist fellow learners.
The repository is organized as follows:
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Day-wise Notes: Contains detailed revision notes for each day of my learning journey. The notes will cover various Machine Learning concepts, algorithms, and techniques, providing explanations, examples, and references for further exploration.
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Day-wise Code: Includes code implementations for each day's learning topic. The code will be written in Python and utilize popular libraries such as scikit-learn, TensorFlow, and PyTorch. You can run the code and experiment with different datasets to deepen your understanding.
If you are new to Machine Learning, I recommend following these steps to get started:
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Clone this repository to your local machine.
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Explore the day-wise notes in the "Day-wise Notes" directory. Start with Day 1 and progress through each day's topic, building your understanding step by step.
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Check out the code implementations in the "Day-wise Code" directory. Each day will have its own code file corresponding to the topic covered. Run the code and experiment with different datasets to gain hands-on experience.
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Check out the free resources
- https://www.youtube.com/playlist?list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU
- https://www.youtube.com/watch?v=ZftI2fEz0Fw&list=PLKnIA16_Rmvbr7zKYQuBfsVkjoLcJgxHH
- https://www.coursera.org/specializations/machine-learning-introduction
While this repository primarily documents my personal learning journey, I welcome contributions from the community. If you have any suggestions, improvements, or would like to add your own code implementations or projects, please feel free to submit a pull request. Let's learn and grow together!
Happy learning!