searchindex.js

Search.setIndex({"alltitles": {"(\u2026)": [[271, "id1"]], "- Data Preparation": [[289, "data-preparation"]], "- Model Initialization": [[289, "model-initialization"]], "- Training Loop": [[289, "training-loop"]], "- Validation Steps": [[289, "validation-steps"]], "1. Accuracy": [[274, "accuracy"], [287, "accuracy"]], "1. Basic Setup": [[274, "basic-setup"], [287, "basic-setup"]], "1. Binary Classification": [[274, "binary-classification"], [287, "binary-classification"]], "1. Continuous vs Discrete Outputs": [[274, "continuous-vs-discrete-outputs"], [287, "continuous-vs-discrete-outputs"]], "1. Correlation Heatmaps": [[273, "correlation-heatmaps"], [286, "correlation-heatmaps"]], "1. Data Loading & Preprocessing": [[282, "data-loading-preprocessing"]], "1. Data Preparation": [[276, "data-preparation"]], "1. Deletion Methods": [[273, "deletion-methods"], [286, "deletion-methods"]], "1. Easy to Understand": [[274, "easy-to-understand"], [287, "easy-to-understand"]], "1. Feature Importance": [[274, "feature-importance"], [287, "feature-importance"]], "1. Feature Selection": [[274, "feature-selection"], [287, "feature-selection"]], "1. Filter Methods": [[273, "filter-methods"], [286, "filter-methods"]], "1. Histograms": [[273, "histograms"], [286, "histograms"]], "1. How do I know this is the right course for me to do?": [[271, "how-do-i-know-this-is-the-right-course-for-me-to-do"]], "1. Identifying Duplicates": [[273, "identifying-duplicates"], [286, "identifying-duplicates"]], "1. Information Flow": [[289, "information-flow"]], "1. Input Processing": [[289, "input-processing"], [289, "id6"]], "1. Learning Rate": [[274, "learning-rate"], [287, "learning-rate"]], "1. Mean Squared Error (MSE)": [[274, "mean-squared-error-mse"], [287, "mean-squared-error-mse"]], "1. Mean, Median, and Mode": [[273, "mean-median-and-mode"], [286, "mean-median-and-mode"]], "1. Min-Max Scaling": [[273, "min-max-scaling"], [286, "min-max-scaling"]], "1. Multiple Trees": [[274, "multiple-trees"], [287, "multiple-trees"]], "1. NumPy Arrays": [[273, "numpy-arrays"], [286, "numpy-arrays"]], "1. Numerical Data": [[273, "numerical-data"], [286, "numerical-data"]], "1. One-Hot Encoding": [[273, "one-hot-encoding"], [286, "one-hot-encoding"]], "1. Parameter Tuning": [[274, "parameter-tuning"], [287, "parameter-tuning"]], "1. Predicting Categories vs Numbers": [[274, "predicting-categories-vs-numbers"], [287, "predicting-categories-vs-numbers"]], "1. Removing Duplicates": [[273, "removing-duplicates"], [286, "removing-duplicates"]], "1. Root Node": [[274, "root-node"], [287, "root-node"]], "1. Scaling Order in Pipeline": [[273, "scaling-order-in-pipeline"], [286, "scaling-order-in-pipeline"]], "1. Sequential Learning": [[274, "sequential-learning"], [287, "sequential-learning"]], "1. Simple Example": [[274, "simple-example"], [287, "simple-example"]], "1. Simple Line Fitting": [[274, "simple-line-fitting"], [287, "simple-line-fitting"]], "1. Single-Layer Neural Network": [[289, "single-layer-neural-network"]], "1. Slope and Intercept": [[274, "slope-and-intercept"], [287, "slope-and-intercept"]], "1. Spam Detection": [[274, "spam-detection"], [287, "spam-detection"]], "1. Statistical Methods": [[273, "statistical-methods"], [286, "statistical-methods"]], "1. Tensor Shape": [[276, "tensor-shape"]], "1. Threshold Values": [[274, "threshold-values"], [287, "threshold-values"]], "1. Train-Test Split": [[274, "train-test-split"], [287, "train-test-split"]], "1. Types of Missing Data": [[273, "types-of-missing-data"], [286, "types-of-missing-data"]], "2 types of Machine Learning Models:": [[272, "types-of-machine-learning-models"], [285, "types-of-machine-learning-models"]], "2. Binary vs Multi-class Classification": [[274, "binary-vs-multi-class-classification"], [287, "binary-vs-multi-class-classification"]], "2. Box Plots": [[273, "box-plots"], [286, "box-plots"]], "2. 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House Price Example": [[274, "house-price-example"], [287, "house-price-example"]], "2. Label Encoding": [[273, "label-encoding"], [286, "label-encoding"]], "2. Layer Calculations": [[289, "layer-calculations"]], "2. Medical Diagnosis": [[274, "medical-diagnosis"], [287, "medical-diagnosis"]], "2. Missing Patterns": [[273, "missing-patterns"], [286, "missing-patterns"]], "2. Model Architecture": [[276, "model-architecture"], [282, "model-architecture"]], "2. Multi-Layer Neural Network": [[289, "multi-layer-neural-network"]], "2. Multiple Features": [[274, "multiple-features"], [287, "multiple-features"]], "2. Out-of-bag Error": [[274, "out-of-bag-error"], [287, "out-of-bag-error"]], "2. Output Range": [[289, "output-range"]], "2. Overfitting Risk": [[274, "overfitting-risk"], [287, "overfitting-risk"]], "2. Pair Plots": [[273, "pair-plots"], [286, "pair-plots"]], "2. Pandas DataFrames & Series": [[273, "pandas-dataframes-series"], [286, "pandas-dataframes-series"]], "2. Parameter Selection": [[274, "parameter-selection"], [287, "parameter-selection"]], "2. Precision": [[274, "precision"], [287, "precision"]], "2. Probability Interpretation": [[274, "probability-interpretation"], [287, "probability-interpretation"]], "2. Probability Output": [[274, "probability-output"], [287, "probability-output"]], "2. R-squared (R\u00b2)": [[274, "r-squared-r2"], [287, "r-squared-r2"]], "2. Real-world Examples": [[274, "real-world-examples"], [287, "real-world-examples"]], "2. Simple Imputation": [[273, "simple-imputation"], [286, "simple-imputation"]], "2. Split Criteria": [[274, "split-criteria"], [287, "split-criteria"]], "2. Standard Deviation": [[273, "standard-deviation"], [286, "standard-deviation"]], "2. Standard Scaling (Z-score)": [[273, "standard-scaling-z-score"], [286, "standard-scaling-z-score"]], "2. Tensor Data Type": [[276, "tensor-data-type"]], "2. Tree Depth": [[274, "tree-depth"], [287, "tree-depth"]], "2. Voting System": [[274, "voting-system"], [287, "voting-system"]], "2. Weak Learners": [[274, "weak-learners"], [287, "weak-learners"]], "2. Wrapper Methods": [[273, "wrapper-methods"], [286, "wrapper-methods"]], "3-Clause BSD License": [[33, "clause-bsd-license"], [78, "clause-bsd-license"], [124, "clause-bsd-license"], [169, "clause-bsd-license"], [214, "clause-bsd-license"], [259, "clause-bsd-license"]], "3. Assumptions": [[274, "assumptions"], [287, "assumptions"]], "3. Bagging Process": [[274, "bagging-process"], [287, "bagging-process"]], "3. Binary Data": [[273, "binary-data"], [286, "binary-data"]], "3. Binary Output": [[274, "binary-output"], [287, "binary-output"]], "3. Binning Numerical Data": [[273, "binning-numerical-data"], [286, "binning-numerical-data"]], "3. Checking Data Balance": [[273, "checking-data-balance"], [286, "checking-data-balance"]], "3. Common Pitfalls": [[274, "common-pitfalls"], [287, "common-pitfalls"]], "3. Computational Efficiency": [[289, "computational-efficiency"]], "3. Credit Approval": [[274, "credit-approval"], [287, "credit-approval"]], "3. Deep Neural Networks (DNNs)": [[289, "deep-neural-networks-dnns"]], "3. Distribution Plots": [[273, "distribution-plots"], [286, "distribution-plots"]], "3. Domain Knowledge": [[273, "domain-knowledge"], [286, "domain-knowledge"]], "3. Embedded Methods": [[273, "embedded-methods"], [286, "embedded-methods"]], "3. Equation Form": [[274, "equation-form"], [287, "equation-form"]], "3. Feature Selection": [[274, "id1"], [287, "id1"]], "3. Forward Pass": [[276, "forward-pass"]], "3. Gradient Boosting": [[274, "gradient-boosting"], [287, "gradient-boosting"]], "3. Holdout Sets": [[274, "holdout-sets"], [287, "holdout-sets"]], "3. Impact Assessment": [[273, "impact-assessment"], [286, "impact-assessment"]], "3. Information Gain": [[273, "information-gain"], [286, "information-gain"]], "3. Leaf Nodes": [[274, "leaf-nodes"], [287, "leaf-nodes"]], "3. 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Decision Boundary": [[274, "decision-boundary"], [287, "decision-boundary"]], "4. Dimensionality Reduction": [[273, "dimensionality-reduction"], [286, "dimensionality-reduction"]], "4. Error Correction": [[274, "error-correction"], [287, "error-correction"]], "4. F1-Score": [[274, "f1-score"], [287, "f1-score"]], "4. Feature Impact": [[274, "feature-impact"], [287, "feature-impact"]], "4. Finding Data Anomalies": [[273, "finding-data-anomalies"], [286, "finding-data-anomalies"]], "4. Input vs Output Types": [[274, "input-vs-output-types"], [287, "input-vs-output-types"]], "4. Iterative Learning": [[289, "iterative-learning"]], "4. Limitations": [[274, "limitations"], [287, "limitations"]], "4. Line Plots": [[273, "line-plots"], [286, "line-plots"]], "4. Line of Best Fit": [[274, "line-of-best-fit"]], "4. Log Transformation": [[273, "log-transformation"], [286, "log-transformation"]], "4. Loss Calculation and Backpropagation": [[276, "loss-calculation-and-backpropagation"]], "4. 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Time Series Data": [[273, "time-series-data"], [286, "time-series-data"]], "4. Time Series Plots": [[273, "time-series-plots"], [286, "time-series-plots"]], "4. Validation Curves": [[274, "validation-curves"], [287, "validation-curves"]], "4. Visualization & Interpretation": [[282, "visualization-interpretation"]], "5. Accessing Gradients": [[276, "accessing-gradients"]], "5. Bar Charts": [[273, "bar-charts"], [286, "bar-charts"]], "5. Confusion Matrix": [[274, "confusion-matrix"], [287, "confusion-matrix"]], "5. Distribution Analysis": [[273, "distribution-analysis"], [286, "distribution-analysis"]], "5. Feature Engineering Basics": [[273, "feature-engineering-basics"], [286, "feature-engineering-basics"]], "5. Fixing Data Types": [[273, "fixing-data-types"], [286, "fixing-data-types"]], "5. Interactive Visualizations": [[273, "interactive-visualizations"], [286, "interactive-visualizations"]], "5. Model Evaluation": [[282, "model-evaluation"]], "5. Power Transformation": [[273, "power-transformation"], [286, "power-transformation"]], "5. Text Data": [[273, "text-data"], [286, "text-data"]], "5. 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199, 200, 202, 214, 219, 224, 244, 245, 247, 259, 264, 269, 288, 289], "caution": 288, "cautiou": 289, "cc": [36, 81, 127, 172, 217, 262], "cc398b": [7, 52, 98, 143, 188, 233], "ccbb44": [6, 51, 97, 142, 187, 232], "cdoubl": 276, "celebr": 288, "cell": [90, 288, 290, 292], "center": [276, 288, 289], "central": 290, "ceo": [274, 287], "certain": [272, 276, 285, 287, 289, 290, 291, 292], "certainli": [274, 287], "certainti": [274, 287], "certik": [36, 81, 127, 172, 217, 262], "cf": [32, 77, 123, 168, 213, 258], "cf222e": [11, 56, 102, 147, 192, 237], "cgohlk": [36, 81, 127, 172, 217, 262], "chair": [288, 289, 290], "chalkboard": 292, "challeng": [90, 276, 290], "chanc": [274, 276, 287, 288, 289], "chang": [42, 87, 133, 178, 223, 268, 273, 274, 276, 286, 287, 289, 290, 291, 292], "changelog": [29, 30, 74, 75, 120, 121, 165, 166, 210, 211, 255, 256], "channel": 288, "chao": 288, "chapel": [36, 81, 127, 172, 217, 262], "chapter": [90, 271], "charact": [1, 29, 46, 74, 92, 120, 137, 165, 182, 210, 227, 255, 273, 286, 288, 292], "characterist": [276, 287, 288, 291, 292], "charg": [22, 28, 33, 35, 37, 67, 73, 78, 80, 82, 113, 119, 124, 126, 128, 158, 164, 169, 171, 173, 203, 209, 214, 216, 218, 248, 254, 259, 261, 263, 290], "charger": 288, "charli": [273, 274, 286, 287], "charset": [1, 31, 46, 76, 92, 122, 137, 167, 182, 212, 227, 257], "chart": 292, "chat": [90, 271], "check": [23, 26, 32, 42, 68, 71, 77, 87, 114, 117, 123, 133, 159, 162, 168, 178, 204, 207, 213, 223, 249, 252, 258, 268, 271, 272, 274, 276, 285, 287, 288, 289, 290, 291], "cheerlead": 288, "chees": [273, 274, 286, 287, 288, 289], "chef": [272, 273, 274, 276, 285, 286, 287, 288, 289, 290], "chemistri": [273, 286], "chernyshov": [36, 81, 127, 172, 217, 262], "chess": [276, 288], "chief": 276, "child": [272, 273, 274, 276, 285, 286, 287, 289, 291], "children": [273, 286], "chines": [274, 287], "chip": [272, 285, 288, 290, 292], "choc": [274, 287], "chocol": [272, 273, 276, 285, 286, 289, 290, 291, 292], 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276, 286, 287, 289, 292], "cm": [26, 71, 117, 162, 207, 252, 273, 286], "cmakelist": [44, 89, 135, 180, 225, 270], "cmap": [26, 71, 117, 162, 207, 252], "cnn": [271, 282], "co": [36, 81, 127, 172, 217, 262], "coach": [273, 286, 289, 290], "coat": 288, "cocoa": [276, 289], "code": [1, 8, 10, 18, 19, 20, 21, 25, 27, 28, 29, 33, 38, 42, 43, 46, 53, 55, 63, 64, 65, 66, 70, 72, 73, 74, 78, 83, 87, 88, 90, 92, 99, 101, 109, 110, 111, 112, 116, 118, 119, 120, 124, 129, 133, 134, 137, 144, 146, 154, 155, 156, 157, 161, 163, 164, 165, 169, 174, 178, 179, 182, 189, 191, 199, 200, 201, 202, 206, 208, 209, 210, 214, 219, 223, 224, 227, 234, 236, 244, 245, 246, 247, 251, 253, 254, 255, 259, 264, 268, 269, 271, 281, 290], "codec": [1, 27, 28, 46, 72, 73, 92, 118, 119, 137, 163, 164, 182, 208, 209, 227, 253, 254], "codecobbl": [36, 81, 127, 172, 217, 262], "coffe": [273, 286, 288], "coin": [274, 287], "coincid": 288, "colab": [90, 271, 281], "cold": [26, 71, 117, 162, 207, 252, 273, 274, 276, 286, 287, 289, 292], "colder": 276, "coldest": [274, 287], "colish": [36, 81, 127, 172, 217, 262], "collabor": 290, "colleagu": [274, 287], "collect": [42, 87, 133, 178, 223, 268, 272, 273, 274, 276, 285, 286, 287, 289, 290, 291, 292], "colomiet": [36, 81, 127, 172, 217, 262], "colon": [1, 46, 92, 137, 182, 227], "color": [26, 71, 117, 162, 207, 252, 273, 274, 276, 286, 287, 288, 289, 290], "colsample_bytre": [274, 287], "column": [273, 276, 286, 290, 292], "com": [27, 33, 34, 36, 37, 72, 78, 79, 81, 82, 90, 118, 124, 125, 127, 128, 163, 169, 170, 172, 173, 208, 214, 215, 217, 218, 253, 259, 260, 262, 263, 273, 274, 276, 281, 282, 286, 287], "combin": [32, 77, 123, 168, 213, 258, 272, 273, 274, 276, 282, 285, 286, 287, 288, 289, 291, 292], "combo": 288, "come": [32, 77, 90, 123, 168, 213, 258, 273, 274, 276, 286, 287, 288, 289, 290, 292], "comedi": [274, 287, 292], "comedian": [274, 287], "comfort": [31, 76, 122, 167, 212, 257, 274, 276, 287], "command": [25, 32, 70, 77, 116, 123, 161, 168, 206, 213, 251, 258, 272, 281, 285, 289, 290, 292], "comment": 276, "commerc": [272, 285], "committe": [274, 276, 287], "common": [1, 46, 92, 137, 182, 227, 272, 285, 288, 290, 291, 292], "commonli": [273, 276, 286], "commonmark": [24, 69, 115, 160, 205, 250], "commun": [288, 290, 292], "compact": 292, "compani": [274, 287, 292], "compar": [273, 274, 276, 282, 286, 287, 288, 289, 290, 291], "comparison": [32, 77, 123, 168, 213, 258, 274, 287], "compass": 289, "compat": [31, 32, 76, 77, 122, 123, 167, 168, 212, 213, 257, 258, 276], "compat32": [1, 46, 92, 137, 182, 227], "competit": [274, 287, 289], "complet": [273, 274, 276, 286, 287, 288, 289, 291, 292], "complex": [90, 271, 272, 273, 274, 276, 285, 286, 287, 288, 289, 290, 291, 292], "complex128": 276, "complex64": 276, "complianc": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243], "compliant": [1, 46, 92, 137, 182, 227], "complic": [271, 274, 276, 287, 288, 289, 290], "compon": [1, 46, 92, 137, 182, 227, 271, 282, 284, 294], "compos": 290, "composit": [273, 286], "comprehens": [271, 289, 291, 292], "compress": [273, 286, 291], "compromis": 289, "comput": [32, 77, 123, 168, 213, 258, 271, 272, 273, 276, 285, 286, 292, 293], "computation": 276, "concept": [90, 271, 272, 282, 283, 285, 290], "conceptu": [1, 46, 92, 137, 182, 227], "concern": [271, 292, 293], "conclus": [276, 289, 291, 292], "conda": [271, 290], "condens": 276, "condit": [18, 19, 21, 22, 28, 33, 35, 37, 38, 43, 63, 64, 66, 67, 73, 78, 80, 82, 83, 88, 109, 110, 112, 113, 119, 124, 126, 128, 129, 134, 154, 155, 157, 158, 164, 169, 171, 173, 174, 179, 199, 200, 202, 203, 209, 214, 216, 218, 219, 224, 244, 245, 247, 248, 254, 259, 261, 263, 264, 269, 274, 276, 287, 288, 289, 290, 291, 292], "condition": 289, "conduct": 276, "confid": [274, 276, 287], "configur": 290, "confirm": 276, "conflict": 271, "conform": [1, 46, 92, 137, 182, 227], "confus": [276, 282, 289], "connect": [22, 28, 33, 35, 37, 67, 73, 78, 80, 82, 113, 119, 124, 126, 128, 158, 164, 169, 171, 173, 203, 209, 214, 216, 218, 248, 254, 259, 261, 263, 274, 276, 287, 288, 291, 292, 293], "connector": 288, "consciou": 288, "consequenti": [18, 19, 21, 33, 38, 43, 63, 64, 66, 78, 83, 88, 109, 110, 112, 124, 129, 134, 154, 155, 157, 169, 174, 179, 199, 200, 202, 214, 219, 224, 244, 245, 247, 259, 264, 269], "conserv": [276, 288], "consid": [32, 77, 90, 123, 168, 213, 258, 273, 274, 276, 286, 287, 288, 289, 290, 291, 292], "consist": [1, 32, 46, 77, 92, 123, 137, 168, 182, 213, 227, 258, 272, 273, 276, 285, 286, 289, 290], "consol": [29, 74, 120, 165, 210, 255], "const": [31, 76, 122, 167, 212, 257], 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124, 126, 128, 129, 134, 154, 155, 157, 158, 164, 169, 171, 173, 174, 179, 199, 200, 202, 203, 209, 214, 216, 218, 219, 224, 244, 245, 247, 248, 254, 259, 261, 263, 264, 269], "contribut": [36, 81, 127, 172, 217, 262, 274, 276, 287, 289, 290, 291, 292], "contributor": [18, 19, 21, 27, 33, 38, 43, 63, 64, 66, 72, 78, 83, 88, 109, 110, 112, 118, 124, 129, 134, 154, 155, 157, 163, 169, 174, 179, 199, 200, 202, 208, 214, 219, 224, 244, 245, 247, 253, 259, 264, 269], "control": [274, 276, 287, 288, 289, 290, 293], "convei": 292, "conveni": [1, 32, 46, 77, 92, 123, 137, 168, 182, 213, 227, 258], "convent": 276, "convers": [273, 286, 290, 292], "convert": [1, 25, 42, 46, 70, 87, 92, 116, 133, 137, 161, 178, 182, 206, 223, 227, 251, 268, 272, 273, 276, 285, 286, 288, 292], "convex": 276, "convolut": [271, 276, 290], "cook": [273, 274, 276, 286, 287, 288, 289, 290], "cookbook": [274, 276, 287, 288, 290], "cooki": [272, 273, 274, 285, 286, 287, 288, 289, 290, 291, 292], "cool": [274, 287, 289], "coolwarm": [26, 71, 117, 162, 207, 252], "coordin": [272, 285, 288, 289, 291, 292], "copi": [22, 28, 32, 33, 35, 37, 67, 73, 77, 78, 80, 82, 113, 119, 123, 124, 126, 128, 158, 164, 168, 169, 171, 173, 203, 209, 213, 214, 216, 218, 248, 254, 258, 259, 261, 263, 273, 286, 290, 291], "copyright": [18, 19, 21, 22, 28, 33, 35, 37, 38, 43, 63, 64, 66, 67, 73, 78, 80, 82, 83, 88, 109, 110, 112, 113, 119, 124, 126, 128, 129, 134, 154, 155, 157, 158, 164, 169, 171, 173, 174, 179, 199, 200, 202, 203, 209, 214, 216, 218, 219, 224, 244, 245, 247, 248, 254, 259, 261, 263, 264, 269], "core": [272, 273, 285, 286, 290, 292], "corlai": [36, 81, 127, 172, 217, 262], "corner": [90, 291], "correct": [273, 276, 286, 289, 290, 292], "correctli": [272, 274, 285, 287, 289, 290, 292], "correspond": [1, 32, 46, 77, 92, 123, 137, 168, 182, 213, 227, 258, 290, 291, 292], "corridor": 288, "cosin": 288, "cost": [273, 276, 286, 288, 293], "costli": 276, "cough": [274, 287, 288], "could": [1, 32, 46, 77, 92, 123, 137, 168, 182, 213, 227, 258, 272, 276, 285, 289, 290, 291, 292], "counselor": 276, "count": [273, 274, 286, 287, 288, 292], "counter": 288, "countri": 288, "coupl": [32, 77, 123, 168, 213, 258], "coupon": 288, "cours": [1, 46, 92, 137, 182, 227, 274, 276, 287], "court": [288, 289], "cover": [276, 289, 291], "cox": [36, 81, 127, 172, 217, 262, 273, 286], "cozi": 288, "cpu": [274, 276, 287], "crack": 289, "craig": [36, 81, 127, 172, 217, 262], "cram": 291, "crash": [274, 276, 287, 289], "creager": [36, 81, 127, 172, 217, 262], "cream": [273, 274, 286, 287, 288], "creat": [1, 26, 29, 42, 46, 71, 74, 87, 90, 92, 117, 120, 133, 137, 162, 165, 178, 182, 207, 210, 223, 227, 252, 255, 268, 271, 272, 273, 282, 285, 286, 288, 289, 291, 292], "creation": [1, 32, 46, 77, 92, 123, 137, 168, 182, 213, 227, 258, 276, 293], "creativ": [276, 289], "credit": [31, 76, 122, 167, 212, 257, 288], "crime": [274, 287], "criteria": [288, 290], "criterion": 276, "critic": [273, 274, 276, 286, 287, 289, 291], 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168, 213, 258, 272, 285, 289, 290, 291, 292], "eas": 290, "easi": [31, 32, 76, 77, 90, 122, 123, 167, 168, 212, 213, 257, 258, 273, 276, 286, 288, 289, 290, 292], "easier": [42, 87, 133, 178, 223, 268, 272, 274, 276, 285, 287, 288, 289, 290, 291, 292], "easili": [273, 276, 286, 289, 290], "eat": [274, 287, 288, 289, 292], "ec8e2c": [9, 54, 100, 145, 190, 235], "econom": [33, 78, 124, 169, 214, 259], "ecosystem": [24, 69, 115, 160, 205, 250, 290], "edg": [276, 288, 289, 290, 293], "edge_label": 276, "edit": [42, 87, 133, 178, 223, 268, 274, 287, 291], "editor": 291, "edu": [36, 81, 127, 172, 217, 262], "eduardo": [36, 81, 127, 172, 217, 262], "eduardooc": [36, 81, 127, 172, 217, 262], "educ": [273, 286], "ee6677": [6, 51, 97, 142, 187, 232], "effect": [27, 72, 118, 163, 208, 253, 273, 286, 288, 289, 290, 291, 292], "effici": [272, 273, 274, 276, 285, 286, 287, 288, 290, 291, 292], "efficientnet": 282, "effort": [274, 287, 289, 290, 291], "egg": [273, 274, 276, 286, 288, 289, 290], 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