🌟 Welcome to my repository showcasing projects from the Machine Learning A-Z™: Hands-On Python & R In Data Science course by Kirill Eremenko and Hadelin de Ponteves on Udemy!
This course was an incredible journey into the world of machine learning, offering both theoretical understanding and practical applications.
✅ Data Preprocessing
✅ Regression: Simple, Multiple, Polynomial, SVR, Decision Tree, Random Forest
✅ Classification: Logistic Regression, KNN, SVM, Naive Bayes, Decision Trees
✅ Clustering: K-Means, Hierarchical Clustering
✅ Association Rule Learning: Apriori, Eclat
✅ Natural Language Processing (NLP)
✅ Deep Learning: ANN, CNN, RNN
✅ Reinforcement Learning: Thompson Sampling, UCB
✅ Dimensionality Reduction: PCA, LDA, Kernel PCA
✅ Model Selection and Boosting: XGBoost
Each topic includes hands-on projects implemented using Python and real-world based datasets, reinforcing theoretical concepts with practical applications.
This repository contains Python implementations for all the topics and algorithms covered in the course.
📁 Association-Rule-Learning/
📁 Classification/
📁 Clustering/
📁 Data-Preprocessing/
📁 Deep-Learning/
📁 Dimensionality-Reduction/
📁 Model-Selection-and-Boosting/
📁 Natural-Language-Processing/
📁 Regression/
📁 Reinforcement-Learning/
📄 certificate.png
📄 README.md
Clone this repository:
git clone https://github.com/sameetpatil5/machine-learning-projects.git
cd machine-learning-projects/Navigate to the desired project folder:
cd Regression/Simple Linear Regression/simple_linear_regression.ipynbRun the notebook.
Proud to have completed this journey and earned the certificate of completion! 🏆
A huge thanks to Kirill Eremenko and Hadelin de Ponteves for their intuitive teaching and comprehensive curriculum.
If you liked this repository, feel free to reach out!
💼 LinkedIn
✍️ Medium
🐦 Twitter
#Python #ArtificialIntelligence #MachineLearning #DataScience #Udemy #DataPreprocessing