help with this machine learning assignment using python and JAX
links for question 1 that hyperlink by "this, this, and this"
1.https://explained.ai/gradient-boosting/
2.https://www.kaggle.com/code/kashnitsky/topic-10-gradient-boosting/notebook
3.https://www.gormanalysis.com/blog/gradient-boosting-explained/
summarize the technique including equations for question 1
for q2
link for the classification task
1.https://www.kaggle.com/code/kashnitsky/topic-10-gradient-boosting?scriptVersionId=37852307&cellId=15
q3
link to EMG dataset
https://archive.ics.uci.edu/ml/datasets/EMG+Physical+Action+Data+Set
link for a demonstration of similar application
https://archive.ics.uci.edu/ml/datasets/EMG+Physical+Action+Data+Set
Electromyography and Gradient Boosting In this assignment you will expand on the Gradient Boosting ensemble prediction method you saw in class by coding it from scratch Background and Documentation (30 points) Make sure you go through this, this and this excellent writeups. Summarise the technique including the equations in a markdown file or notebook. Coding from scratch using JAX (30 points) Neh Using libraries from the JAX ecosystem, code gradient boosting from scratch using the clipped cosinusoidal dataset for the classification task. EMG Dataset (40 points) mh rhe mE BL Tier non fn @ ® sz Yomonofthmaitamt from terest rloriews of ha dil re fend mend trode placement with s ground cectode Apply your gradient boosting implementation to the EMG dataset - for a demonstration of a similar application see this tutorial