My Journey Through Python, Machine Learning, and Future Deep Learning
Welcome to my journey of mastering Artificial Intelligence and Machine Learning! This repository links all the languages and projects I've worked on, starting from Python fundamentals, progressing through Machine Learning techniques, and with Deep Learning coming up next.
With 38+ commits, this repository showcases my Python journey, including foundational concepts, data structures, and algorithms. It also includes practical statistics implementations to reinforce my understanding of data science principles.
With 25+ commits, this repository highlights my exploration of Machine Learning concepts. It contains Jupyter Notebook implementations of various ML algorithms, such as regression, classification, and clustering.
An end-to-end machine learning project focused on detecting faults in semiconductor wafers using sensor data from 59 features. Includes a complete ML pipeline with data processing, model training, evaluation, and a future plan for deployment on AWS.
With structured notebooks and notes, this repository captures my journey through Deep Learning concepts, featuring hands-on implementations of neural networks, CNNs, RNNs, and more.
For those interested in more in-depth learning, I have also compiled my handwritten notes on Statistics and Machine Learning, available through the link below: Handwritten Notes by Yash Pandey
This repository represents the entire journey from my early days with Python to my current work with Machine Learning, and eventually, the next step in Deep Learning. It is a continuous learning path, and I aim to update it regularly as I explore more advanced techniques in the AIML field.