مسیر یادگیری Machine Learning

Step by step guide to becoming a Machine Learning Engineer in 2025

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ElasticNet RegularizationValidation TechniquesBack PropagationRidgeMatrix & Matrix OperationsAdvanced Concepts in MLUnsupervised LearningGradient, Jacobian, HessianEigenvalues, DiagonalizationAccuracyNeural Network (NN) BasicsActor-Critic MethodsStatisticsMetrics to EvaluateSupervised LearningData CleaningTrain - Test DataReinforcement LearningMachine LearningLog LossBayes TheoremUnsupervised LearningPyTorchLinear AlgebraPerceptron, Multi-layer PerceptronsWhat is Model Evaluation?What is Unsupervised Learning?Deep-Q NetworksPaddingLogistic Regression What is Supervised Learning?Deep Learning LibrariesROC-AUCDecision Trees, Random ForestProgramming Fundamentals Data LoadingConvolutional Neural NetworkOverlappingSkills and ResponsibilitiesEmbeddingsClusteringFind the interactive version ofthis roadmap and more roadmaps atClassificationFeature SelectionInternetSupervised LearningScalars, Vectors, TensorsModel SelectionVariables and Data TypesRecallFunctions, Builtin FunctionsMobile AppsInferential StatisticsLoopsImage ClassificationExclusiveRecommendation SystemsWhat is Reinforcement Learning?LassoData CollectionF1-ScoreWhat is an ML Engineer?ExceptionsApplications of CNNsModel EvaluationML Engineer vs AI EngineerLOOCVRegressionDerivatives, Partial DerivativesRecurrent Neural NetworksPolynomial RegressionAI & Data ScientistBasic SyntaxRELATED ROADMAPS› AI Engineer Roadmap› MLOps Roadmap› AI and Data Scientist RoadmapFeature Scaling & Normalizationkaar2.irPoolingMathematical FoundationsGenerative Adversarial NetworksImage SegmentationMulti-head AttentionHierarchicalChain rule of derivationImage & Video RecognitionPre-requisitesSupport Vector MachinesGradient Boosting MachinesNatural Language ProcessingExcelJSONLoss FunctionsIoTMLOpsAutoencodersPrincipal Component Analysis LSTMSelf-supervised LearningRNNForward propagationTuningPreprocessing TechniquesIntroductionPrecisionConvolutionCSVGraphs & ChartsReinforcement LearningNumpyObject Oriented ProgrammingConditionalsTypes of Machine LearningData CleaningDiscrete MathematicsAlso visit the following related roadmapsData SourcesSelf-AttentionAutoencodersMatplotlibConfusion MatrixBasic conceptsRandom Variances, PDFsBasics of ProbabilityPandasLemmatizationDeep LearningPython RoadmapPolicy GradientTokenizationPythonOther Data FormatsData StructuresTransformersTensorFlowActivation FunctionsWhat is Machine Learning?Attention ModelsAPIsLinear AlgebraParquetExplainable AIAttention MechanismsData FormatsFeature EngineeringStemmingAI AgentsPredictionDatabases (SQL, No-SQL)Why is it important?Dimensionality ReductionProbabilisticK-Fold Cross ValidationSeabornData PreparationCalculusTypes of DistributionQ-LearningK-Nearest Neighbors (KNN)AI EngineerLinear RegressionDeterminants, inverse of MatrixDimensionality ReductionEssential librariesSingular Value DecompositionSemi-supervised LearningScikit-learnStridesDeep Learning ArchitecturesDescriptive StatisticsMachine LearningKerasScikit-learnGRU