README.md

Machine-Learning-Tutorial

You can watch the tutorial on SwAt1563 channel

PART 1 NLTK

1. stopwrods
2. clean text - punctuation
3. swear words
4. roots

PART 2 panda

1. panda - info - percentage
2. split data
3. show information gain
4. plot information gain

PART 3 bias feature

1. bias feature

PART 4 CountVectorizer

1. naive bias MultionmialNB - CountVectorizer

PART 5 WITH JUST TEXT FEATURES

1. preprocessing
2. decision tree
3. network MLP
4. naive bias Gaussian
5. show information gain
6. accuracy scores - confusion matrix

PART 6 WITH JUST FILE FEATURES

1. decision tree
2. network MLP
3. naive bias Gaussian
4. show information gain
5. accuracy scores - confusion matrix

Cows Detection Models

1. Load Images
2. Features Vector Extraction
3. Convert Images to Patches
4. Convert Patches to Images
5. get Results
6. Confusion matrix
7. Cross Validation
8. KNN Model
9. Decision Tree Model
10. Logistic Regression Model
11. Random Forest Model
12. Gradient Boosting Model