MachineLearning.md (6276B)
1 # Machine Learning 2 3 Links to ML Notes 4 5 **Definition:** Field of study that gives computers the ability to learn without being explicitly programmed. 6 7 - [Deep Learning](DeepLearning.md) 8 9 ## Deep Learning With Python (Chollet) 10 11 #### Ch 1 (What is DL) 12 13 * [Representation Learning](RepresentationLearning.md) 14 * [Loss Function](LossFunction.md) 15 * [Utility Function](UtilityFunction.md) 16 17 #### Ch 2 (Maths behind DL) 18 19 * [Optimizer](Optimizer.md) 20 * [Transpose](Transpose.md) 21 * [Bias](Bias.md) 22 * [Weight](Weight.md) 23 24 ## ISL Python 25 26 #### Ch 2 27 28 - [Inference](Inference.md) 29 - [Prediction](Prediction.md) 30 31 ## Math for Machine Learning 32 33 #### Ch 2.2 34 35 - [Matrix Multiplication](MatrixMultiplication.md) 36 - [Hadamard Product](HadamardProduct.md) 37 - [Identity Matrix](IdentityMatrix.md) 38 - [Associative](Associative.md) 39 - [Distributive](Distributive.md) 40 - [Commutative](Commutative.md) 41 - [Inverse Transformation](InverseTransformation.md) 42 - [Transpose](Transpose.md) 43 - [Symmetric Matrix](SymmetricMatrix.md) 44 - [Linear Combination](LinearCombination.md) 45 - [Particular Solution](ParticularSolution.md) 46 - [General Solution](GeneralSolution.md) 47 - [Elementary Transformations](ElementaryTransformations.md) 48 - [Row Echelon Form](RowEchelonForm.md) 49 - [Basic Variables](BasicVariables.md) 50 - [Free Variables](FreeVariables.md) 51 - [Reduced Row Echelon Form](ReducedRowEchelonForm.md) 52 - [Gaussian Elimination](GaussianElimination.md) 53 - [Minus One Trick](MinusOneTrick.md) 54 55 ## ML Categories 56 57 - [Supervised Learning](SupervisedLearning.md) 58 - [Semi Supervised Learning](SemiSupervisedLearning.md) 59 - [Self Supervised Learning](SelfSupervisedLearning.md) 60 - [Unsupervised Learning](UnsupervisedLearning.md) 61 - [Reinforcement Learning](ReinforcementLearning.md) 62 - [Instance Based Learning](InstanceBasedLearning.md) 63 - [Model Based Learning](ModelBasedLearning.md) 64 65 ## Concepts 66 67 - [AI Safety](AISafety.md) 68 - [Regression Problem](RegressionProblem.md) 69 - [Transfer Learning](TransferLearning.md) 70 - [Visualization Algorithm](VisualizationAlgorithm.md) 71 - [Dimensionality Reduction](DimensionalityReduction.md) 72 - [Anomaly Detection](AnomalyDetection.md) 73 - [Novelty Detection](NoveltyDetection.md) 74 - [Rule Learning](RuleLearning.md) 75 - [Linear Regression](LinearRegression.md) 76 - [Gradient Descent](GradientDescent.md) 77 - [Classification Problem](ClassificationProblem.md) 78 - [Support Vector Machine](SupportVectorMachine.md) 79 - [Clustering Algorithms](ClusteringAlgorithms.md) 80 - [Eigen Vector](EigenVector.md) 81 - [NLP](NLP.md) 82 - [NLU](NLU.md) 83 - [Feature](Feature.md) 84 - [Offline Learning](OfflineLearning.md) 85 - [Online Learning](OnlineLearning.md) 86 - [KNearest Neighbor](KNearestNeighbor.md) 87 - [Overfitting](Overfitting.md) 88 - [Underfitting](Underfitting.md) 89 - [Generalization Error](GeneralizationError.md) 90 - [RMSE](RMSE.md) 91 - [MAE](MAE.md) 92 - [Stratified Sampling](StratifiedSampling.md) 93 - [Correlation Coefficient](CorrelationCoefficient.md) 94 - [Logistic Regression](LogisticRegression.md) 95 - [Imputation](Imputation.md) 96 - [One Hot Encoding](OneHotEncoding.md) 97 - [Label Encoding](LabelEncoding.md) 98 - [Target Encoding](TargetEncoding.md) 99 - [Hyperparameter](Hyperparameter.md) 100 - [Feature Scaling](FeatureScaling.md) 101 - [Standardization](Standardization.md) 102 - [Min Max Scaling](MinMaxScaling.md) 103 - [Ordinary Least Squares](OrdinaryLeastSquares.md) 104 - [Radial Basis Function](RadialBasisFunction.md) 105 - [KMeans](KMeans.md) 106 - [Stochastic Algorithm](StochasticAlgorithm.md) 107 - [Ensembles](Ensembles.md) 108 - [Confusion Matrix](ConfusionMatrix.md) 109 - [Cross Validation](CrossValidation.md) 110 - [Precision](Precision.md) 111 - [True Positive Rate](TruePositiveRate.md) 112 - [Harmonic Mean](HarmonicMean.md) 113 - [Accuracy](Accuracy.md) 114 - [Decision Threshold](DecisionThreshold.md) 115 - [ROC](ROC.md) 116 - [Multiclass Classifier](MulticlassClassifier.md) 117 - [One Versus All](OneVersusAll.md) 118 - [One Versus One](OneVersusOne.md) 119 - [Multilabel Classification](MultilabelClassification.md) 120 - [Multioutput Classification](MultioutputClassification.md) 121 - [Partial Derivative](PartialDerivative.md) 122 - [Ridge Regression](RidgeRegression.md) 123 - [Lasso Regression](LassoRegression.md) 124 - [Elastic Net Regression](ElasticNetRegression.md) 125 - [Early Stopping](EarlyStopping.md) 126 - [Softmax Regression](SoftmaxRegression.md) 127 - [SVM](SVM.md) 128 - [Decision Trees](DecisionTrees.md) 129 - [Similarity Feature](SimilarityFeature.md) 130 - [CART](CART.md) 131 - [Random Forest](RandomForest.md) 132 - [Voting Classifiers](VotingClassifiers.md) 133 - [Bagging](Bagging.md) 134 - [Pasting](Pasting.md) 135 - [Bias](Bias.md) 136 - [Variance](Variance.md) 137 - [Out Of Bag](OutOfBag.md) 138 - [Random Patches](RandomPatches.md) 139 - [Random Subspaces](RandomSubspaces.md) 140 - [Extra Trees](ExtraTrees.md) 141 - [Ada Boost](AdaBoost.md) 142 - [Gradient Boosting](GradientBoosting.md) 143 - [Histogram Based Gradient Boosting](HistogramBasedGradientBoosting.md) 144 - [Stacking](Stacking.md) 145 - [Projection](Projection.md) 146 - [Subspace](Subspace.md) 147 - [Manifold Learning](ManifoldLearning.md) 148 - [PCA](PCA.md) 149 - [Random Projection](RandomProjection.md) 150 - [LLE](LLE.md) 151 - [Affinity](Affinity.md) 152 - [Segmentation](Segmentation.md) 153 - [DBSCAN](DBSCAN.md) 154 - [Gaussian Mixture Models](GaussianMixtureModels.md) 155 - [Neural Networks](NeuralNetworks.md) 156 - [Perceptrons](Perceptrons.md) 157 - [Backpropagation](Backpropagation.md) 158 - [MLP](MLP.md) 159 - [Wide And Deep NN](WideAndDeepNN.md) 160 - [Categorical Cross Entropy](CategoricalCrossEntropy.md) 161 - [Vanishing Gradients](VanishingGradients.md) 162 - [Exploding Gradients](ExplodingGradients.md) 163 - [Unstable Gradients](UnstableGradients.md) 164 - [Leaky Re LU](LeakyReLU.md) 165 - [Gradient Clipping](GradientClipping.md) 166 - [Batch Normalization](BatchNormalization.md) 167 - [Pretrained Models](PretrainedModels.md) 168 - [Unsupervised Pretraining](UnsupervisedPretraining.md) 169 - [Autoencoder](Autoencoder.md) 170 - [Optimizer](Optimizer.md) 171 - [Momentum](Momentum.md) 172 - [NAG](NAG.md) 173 - [Ada Grad](AdaGrad.md) 174 - [Adam](Adam.md) 175 - [Dropout](Dropout.md) 176 - [Max Norm Regularization](MaxNormRegularization.md) 177 - [Tensor](Tensor.md) 178 - [Transpose](Transpose.md) 179 - [CNN](CNN.md) 180 - [Naive Bayes](NaiveBayes.md) 181 - [Embedding](Embedding.md) 182 - [Representation Learning](RepresentationLearning.md) 183 - [Pooling Layers](PoolingLayers.md) 184 - [Data Augmentation](DataAugmentation.md) 185 - [SMOTE](SMOTE.md) 186 - [Latent Space](LatentSpace.md) 187 - [Shapley Value](ShapleyValue.md)