Udemy-Machine-Learning-A-Z

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Udemy-Machine-Learning-A-Z

★ 22 Open GitHub ↗

Machine Learning Course By Kirill Eremenko

// repository documentation

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# Udemy Machine Learning A-Z

![the-future-of-machine-learning-is-in-finance](https://user-images.githubusercontent.com/29937202/42225404-25ff61e8-7efa-11e8-849e-046c410c801b.jpg)

### By:Kirill Eremenko
``` [Data Scientist & Forex Systems Expert]```
 
### Content
 
### Part 1:[Data Preprocessing](https://github.com/sam2702/Udemy-Machine-Learning-A-Z/tree/master/Data_Preprocessing)
 
### Part 2:[Regression](https://github.com/sam2702/Udemy-Machine-Learning-A-Z/tree/master/Regression) 
```
•Simple Linear Regression
•Multiple Linear Regression
•Polynomial Regression
•Support Vector Regression(SVR)
•Decision Tree Regression
•Random Forest Regression
•Evaluating Regression Models Performance
```
### Part 3:[Classification](https://github.com/sam2702/Udemy-Machine-Learning-A-Z/tree/master/Classification)
```
•Logistic Regression
•K-Nearest Neighbors (K-NN)
•Support Vector Machine (SVM)
•Kernel SVM
•Naive Bayes
•Decision Tree Classification
•Random Forest Classification
•Evaluating Classification Models Performance
```
### Part 4:[Clustering](https://github.com/sam2702/Udemy-Machine-Learning-A-Z/tree/master/Clustering)
```
•K-Means Clustering
•Hierarchical Clustering
```
### Part 5:[Association Rule Learning](https://github.com/sam2702/Udemy-Machine-Learning-A-Z/tree/master/Association%20Rule%20Learning/Apriori_Python)
```
•Apriori
•Eclat
```
### Part 6:[Reinforcement Learning](https://github.com/sam2702/Udemy-Machine-Learning-A-Z/tree/master/Reinforcement%20Learning)
```
•Upper Confidence Bound (UCB)
•Thompson Sampling
```
### Part 7:[Natural Language Processing](https://github.com/sam2702/Udemy-Machine-Learning-A-Z/tree/master/Natural_Language_Processing)

### Part 8:[Deep Learning](https://github.com/sam2702/Udemy-Machine-Learning-A-Z/tree/master/Deep%20Learning) 
```
•Artificial Neural Networks
•Convolutional Neural Networks
```
### Part 9:[Dimensionality Reduction](https://github.com/sam2702/Udemy-Machine-Learning-A-Z/tree/master/Dimensionality%20Reduction) 
```
•Principal Component Analysis (PCA)
•Linear Discriminant Analysis (LDA)
•Kernel PCA
```
### Part 10:[Model Selection & Boosting](https://github.com/sam2702/Udemy-Machine-Learning-A-Z/tree/master/Model%20Selection%20%26%20Boosting) 
```
•Model Selection
•XGBoost
```

Udemy-Machine-Learning-A-Z

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