Hazim-HF / Machine-Learning Public

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This repository contains materials and implementations related to machine learning concepts, techniques, and algorithms. The focus is on building self-learning computer systems that improve through experience and data. The course explores fundamental and advanced topics in machine learning, with applications in Big Data across various fields.

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Name		Name	Last commit message	Last commit date
Latest commit History 37 Commits
.idea		.idea
.ipynb_checkpoints		.ipynb_checkpoints
.vscode		.vscode
00. Proforma		00. Proforma
01. Introduction to Machine Learning		01. Introduction to Machine Learning
02. Linear Regression		02. Linear Regression
03. Classification		03. Classification
04. Resampling Methods		04. Resampling Methods
05. Linear Model Selection		05. Linear Model Selection
06. Nonlinear Models		06. Nonlinear Models
07. Moving Beyond Linearity		07. Moving Beyond Linearity
08. Tree Based Methods		08. Tree Based Methods
09. Support Vector Machine		09. Support Vector Machine
10. Unsupervised Learning		10. Unsupervised Learning
11. Clustering (Unsupervised Learning)		11. Clustering (Unsupervised Learning)
12. Hierarchical Clustering (Unsupervised Learning)		12. Hierarchical Clustering (Unsupervised Learning)
13. Neural Network		13. Neural Network
14. Deep Learning		14. Deep Learning
Books		Books
Data		Data
Project - Assignment 2		Project - Assignment 2
Project		Project
PyCharm		PyCharm
Self		Self
Slide		Slide
Test		Test
images		images
tf_env		tf_env
.gitignore		.gitignore
ML.html		ML.html
ML.ipynb		ML.ipynb
ML.pdf		ML.pdf
ML.py		ML.py
Machine Learning [Autosaved].pptx		Machine Learning [Autosaved].pptx
Machine Learning.pptx		Machine Learning.pptx
README.md		README.md
Study.ipynb		Study.ipynb
boston_tree.dot		boston_tree.dot
carseat_tree.dot		carseat_tree.dot
carseat_tree.png		carseat_tree.png
clustering.csv		clustering.csv
images.rar		images.rar
images2.rar		images2.rar
model.csv		model.csv
models.csv		models.csv
test.ipynb		test.ipynb