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2 | 2 |
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3 | 3 | - [Introduction to scikit-learn](sklearn-introduction.md) |
4 | 4 | - [Binomial Distribution](binomial-distribution.md) |
| 5 | +- [Naive Bayes](naive-bayes.md) |
5 | 6 | - [Regression in Machine Learning](regression.md) |
6 | 7 | - [Polynomial Regression](polynomial-regression.md) |
7 | 8 | - [Confusion Matrix](confusion-matrix.md) |
8 | 9 | - [Decision Tree Learning](decision-tree.md) |
9 | 10 | - [Random Forest](random-forest.md) |
10 | 11 | - [Support Vector Machine Algorithm](support-vector-machine.md) |
11 | | -- [Artificial Neural Network from the Ground Up](ann.md) |
12 | | -- [Introduction To Convolutional Neural Networks (CNNs)](intro-to-cnn.md) |
13 | | -- [TensorFlow](tensorflow.md) |
14 | | -- [PyTorch](pytorch.md) |
15 | 12 | - [Ensemble Learning](ensemble-learning.md) |
16 | 13 | - [Types of optimizers](types-of-optimizers.md) |
17 | 14 | - [Logistic Regression](logistic-regression.md) |
18 | 15 | - [Types_of_Cost_Functions](cost-functions.md) |
19 | 16 | - [Clustering](clustering.md) |
20 | 17 | - [Hierarchical Clustering](hierarchical-clustering.md) |
21 | 18 | - [Grid Search](grid-search.md) |
22 | | -- [Transformers](transformers.md) |
23 | 19 | - [K-Means](kmeans.md) |
24 | 20 | - [K-nearest neighbor (KNN)](knn.md) |
25 | | -<<<<<<< RL |
| 21 | +- [Xgboost](xgboost.md) |
| 22 | +- [Artificial Neural Network from the Ground Up](ann.md) |
| 23 | +- [Introduction To Convolutional Neural Networks (CNNs)](intro-to-cnn.md) |
| 24 | +- [TensorFlow](tensorflow.md) |
| 25 | +- [PyTorch](pytorch.md) |
| 26 | +- [PyTorch Fundamentals](pytorch-fundamentals.md) |
| 27 | +- [Transformers](transformers.md) |
26 | 28 | - [Reinforcement Learning](reinforcement-learning.md) |
27 | | -======= |
28 | | -- [Naive Bayes](naive-bayes.md) |
29 | 29 | - [Neural network regression](neural-network-regression.md) |
30 | | -- [PyTorch Fundamentals](pytorch-fundamentals.md) |
31 | | -- [Xgboost](xgboost.md) |
32 | | ->>>>>>> main |
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