kopia lustrzana https://github.com/animator/learn-python
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- [Introduction to scikit-learn](sklearn-introduction.md)
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- [Binomial Distribution](binomial-distribution.md)
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- [Naive Bayes](naive-bayes.md)
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- [Regression in Machine Learning](regression.md)
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- [Polynomial Regression](polynomial-regression.md)
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- [Confusion Matrix](confusion-matrix.md)
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- [Decision Tree Learning](decision-tree.md)
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- [Random Forest](random-forest.md)
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- [Support Vector Machine Algorithm](support-vector-machine.md)
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- [Artificial Neural Network from the Ground Up](ann.md)
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- [Introduction To Convolutional Neural Networks (CNNs)](intro-to-cnn.md)
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- [TensorFlow](tensorflow.md)
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- [PyTorch](pytorch.md)
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- [Ensemble Learning](ensemble-learning.md)
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- [Types of optimizers](types-of-optimizers.md)
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- [Logistic Regression](logistic-regression.md)
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- [Clustering](clustering.md)
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- [Hierarchical Clustering](hierarchical-clustering.md)
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- [Grid Search](grid-search.md)
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- [Transformers](transformers.md)
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- [K-Means](kmeans.md)
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- [K-nearest neighbor (KNN)](knn.md)
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<<<<<<< RL
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- [Reinforcement Learning](reinforcement-learning.md)
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=======
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- [Naive Bayes](naive-bayes.md)
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- [Neural network regression](neural-network-regression.md)
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- [PyTorch Fundamentals](pytorch-fundamentals.md)
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- [Xgboost](xgboost.md)
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>>>>>>> main
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- [Artificial Neural Network from the Ground Up](ann.md)
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- [Introduction To Convolutional Neural Networks (CNNs)](intro-to-cnn.md)
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- [TensorFlow](tensorflow.md)
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- [PyTorch](pytorch.md)
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- [PyTorch Fundamentals](pytorch-fundamentals.md)
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- [Transformers](transformers.md)
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- [Reinforcement Learning](reinforcement-learning.md)
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- [Neural network regression](neural-network-regression.md)
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