CourseClub Me Coursera Machine Learning Specialization Andrew Ng | E70480F15339F4380B9B6D36330F888C79ED5231

CourseClub Me Coursera Machine Learning Specialization Andrew Ng

Name	[CourseClub.Me] Coursera – Machine Learning Specialization (Andrew Ng)	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	1.7 GB
Total Files	461
Last Seen	2025-07-19 00:26
Hash	E70480F15339F4380B9B6D36330F888C79ED5231

/.../01_neural-networks-intuition/
01_welcome.en.srt	5.5 KB
01_welcome.en.txt	2.9 KB
01_welcome.mp4	11.2 MB
02_neurons-and-the-brain.en.srt	18.7 KB
02_neurons-and-the-brain.en.txt	9.7 KB
02_neurons-and-the-brain.mp4	28.2 MB
03_demand-prediction.en.srt	27.2 KB
03_demand-prediction.en.txt	14.3 KB
03_demand-prediction.mp4	30.9 MB
04_example-recognizing-images.en.srt	10.4 KB
04_example-recognizing-images.en.txt	5.5 KB
04_example-recognizing-images.mp4	15.3 MB
/.../02_neural-network-model/
01_neural-network-layer.en.srt	13.3 KB
01_neural-network-layer.en.txt	7.0 KB
01_neural-network-layer.mp4	21.4 MB
02_more-complex-neural-networks.en.srt	12.0 KB
02_more-complex-neural-networks.en.txt	6.2 KB
02_more-complex-neural-networks.mp4	17.9 MB
03_inference-making-predictions-forward-propagation.en.srt	7.1 KB
03_inference-making-predictions-forward-propagation.en.txt	4.4 KB
03_inference-making-predictions-forward-propagation.mp4	13.2 MB
/.../03_tensorflow-implementation/
01_inference-in-code.en.srt	10.3 KB
01_inference-in-code.en.txt	5.4 KB
01_inference-in-code.mp4	17.6 MB
02_data-in-tensorflow.en.srt	13.5 KB
02_data-in-tensorflow.en.txt	8.5 KB
02_data-in-tensorflow.mp4	26.0 MB
03_building-a-neural-network.en.srt	11.0 KB
03_building-a-neural-network.en.txt	7.0 KB
03_building-a-neural-network.mp4	25.6 MB
/.../04_neural-network-implementation-in-python/
01_forward-prop-in-a-single-layer.en.srt	6.2 KB
01_forward-prop-in-a-single-layer.en.txt	3.9 KB
01_forward-prop-in-a-single-layer.mp4	13.0 MB
02_general-implementation-of-forward-propagation.en.srt	11.9 KB
02_general-implementation-of-forward-propagation.en.txt	6.2 KB
02_general-implementation-of-forward-propagation.mp4	22.4 MB
/.../05_speculations-on-artificial-general-intelligence-agi/
01_is-there-a-path-to-agi.en.srt	16.8 KB
01_is-there-a-path-to-agi.en.txt	8.8 KB
01_is-there-a-path-to-agi.mp4	29.5 MB
/.../06_vectorization-optional/
01_how-neural-networks-are-implemented-efficiently.en.srt	6.3 KB
01_how-neural-networks-are-implemented-efficiently.en.txt	3.2 KB
01_how-neural-networks-are-implemented-efficiently.mp4	14.4 MB
02_matrix-multiplication.en.srt	12.6 KB
02_matrix-multiplication.en.txt	6.5 KB
02_matrix-multiplication.mp4	16.7 MB
03_matrix-multiplication-rules.en.srt	11.7 KB
03_matrix-multiplication-rules.en.txt	7.3 KB
03_matrix-multiplication-rules.mp4	19.4 MB
04_matrix-multiplication-code.en.srt	9.0 KB
04_matrix-multiplication-code.en.txt	4.7 KB
04_matrix-multiplication-code.mp4	14.0 MB
/.../01_neural-network-training/
01_tensorflow-implementation.en.srt	6.1 KB
01_tensorflow-implementation.en.txt	3.2 KB
01_tensorflow-implementation.mp4	11.9 MB
02_training-details.en.srt	21.4 KB
02_training-details.en.txt	11.2 KB
02_training-details.mp4	25.3 MB
/.../02_activation-functions/
01_alternatives-to-the-sigmoid-activation.en.srt	7.0 KB
01_alternatives-to-the-sigmoid-activation.en.txt	4.4 KB
01_alternatives-to-the-sigmoid-activation.mp4	12.5 MB
02_choosing-activation-functions.en.srt	14.1 KB
02_choosing-activation-functions.en.txt	7.4 KB
02_choosing-activation-functions.mp4	24.5 MB
03_why-do-we-need-activation-functions.en.srt	7.8 KB
03_why-do-we-need-activation-functions.en.txt	4.1 KB
03_why-do-we-need-activation-functions.mp4	13.6 MB
/.../03_multiclass-classification/
01_multiclass.en.srt	4.4 KB
01_multiclass.en.txt	2.8 KB
01_multiclass.mp4	8.8 MB
02_softmax.en.srt	15.7 KB
02_softmax.en.txt	8.1 KB
02_softmax.mp4	21.7 MB
03_neural-network-with-softmax-output.en.srt	9.3 KB
03_neural-network-with-softmax-output.en.txt	5.9 KB
03_neural-network-with-softmax-output.mp4	15.8 MB
04_improved-implementation-of-softmax.en.srt	13.7 KB
04_improved-implementation-of-softmax.en.txt	7.2 KB
04_improved-implementation-of-softmax.mp4	18.7 MB
05_classification-with-multiple-outputs-optional.en.srt	6.9 KB
05_classification-with-multiple-outputs-optional.en.txt	3.7 KB
05_classification-with-multiple-outputs-optional.mp4	13.5 MB
/.../04_additional-neural-network-concepts/
01_advanced-optimization.en.srt	10.8 KB
01_advanced-optimization.en.txt	5.7 KB
01_advanced-optimization.mp4	16.3 MB
02_additional-layer-types.en.srt	11.6 KB
02_additional-layer-types.en.txt	7.4 KB
02_additional-layer-types.mp4	23.2 MB
/.../01_advice-for-applying-machine-learning/
01_deciding-what-to-try-next.en.srt	6.9 KB
01_deciding-what-to-try-next.en.txt	3.6 KB
01_deciding-what-to-try-next.mp4	13.5 MB
02_evaluating-a-model.en.srt	13.1 KB
02_evaluating-a-model.en.txt	8.3 KB
02_evaluating-a-model.mp4	24.8 MB
/.../02_bias-and-variance/
01_diagnosing-bias-and-variance.en.srt	18.3 KB
01_diagnosing-bias-and-variance.en.txt	9.5 KB
01_diagnosing-bias-and-variance.mp4	25.3 MB
02_regularization-and-bias-variance.en.srt	16.7 KB
02_regularization-and-bias-variance.en.txt	8.5 KB
02_regularization-and-bias-variance.mp4	26.4 MB
03_establishing-a-baseline-level-of-performance.en.srt	16.3 KB
03_establishing-a-baseline-level-of-performance.en.txt	8.5 KB
03_establishing-a-baseline-level-of-performance.mp4	22.9 MB
04_learning-curves.en.srt	20.5 KB
04_learning-curves.en.txt	10.7 KB
04_learning-curves.mp4	29.4 MB
05_deciding-what-to-try-next-revisited.en.srt	14.9 KB
05_deciding-what-to-try-next-revisited.en.txt	7.9 KB
05_deciding-what-to-try-next-revisited.mp4	29.4 MB
06_bias-variance-and-neural-networks.en.srt	14.9 KB
06_bias-variance-and-neural-networks.en.txt	9.7 KB
06_bias-variance-and-neural-networks.mp4	28.2 MB
/.../03_machine-learning-development-process/
01_iterative-loop-of-ml-development.en.srt	12.4 KB
01_iterative-loop-of-ml-development.en.txt	6.6 KB
01_iterative-loop-of-ml-development.mp4	15.5 MB
02_error-analysis.en.srt	13.5 KB
02_error-analysis.en.txt	7.2 KB
02_error-analysis.mp4	18.4 MB
03_adding-data.en.srt	19.5 KB
03_adding-data.en.txt	12.4 KB
03_adding-data.mp4	34.3 MB
05_full-cycle-of-a-machine-learning-project.en.srt	0.0 KB
05_full-cycle-of-a-machine-learning-project.en.txt	0.0 KB
05_full-cycle-of-a-machine-learning-project.mp4	0.0 KB
06_fairness-bias-and-ethics.en.srt	13.7 KB
06_fairness-bias-and-ethics.en.txt	8.9 KB
06_fairness-bias-and-ethics.mp4	26.6 MB
/.../04_skewed-datasets-optional/
01_error-metrics-for-skewed-datasets.en.srt	17.4 KB
01_error-metrics-for-skewed-datasets.en.txt	9.1 KB
01_error-metrics-for-skewed-datasets.mp4	23.7 MB
02_trading-off-precision-and-recall.en.srt	18.7 KB
02_trading-off-precision-and-recall.en.txt	9.8 KB
02_trading-off-precision-and-recall.mp4	27.9 MB
/.../01_decision-trees/
01_decision-tree-model.en.srt	11.1 KB
01_decision-tree-model.en.txt	5.8 KB
01_decision-tree-model.mp4	15.5 MB
02_learning-process.en.srt	18.5 KB
02_learning-process.en.txt	9.7 KB
02_learning-process.mp4	30.4 MB
/.../02_decision-tree-learning/
01_measuring-purity.en.srt	10.4 KB
01_measuring-purity.en.txt	5.5 KB
01_measuring-purity.mp4	19.0 MB
02_choosing-a-split-information-gain.en.srt	17.8 KB
02_choosing-a-split-information-gain.en.txt	9.2 KB
02_choosing-a-split-information-gain.mp4	24.9 MB
03_putting-it-together.en.srt	14.9 KB
03_putting-it-together.en.txt	7.9 KB
03_putting-it-together.mp4	19.3 MB
04_using-one-hot-encoding-of-categorical-features.en.srt	6.8 KB
04_using-one-hot-encoding-of-categorical-features.en.txt	4.4 KB
04_using-one-hot-encoding-of-categorical-features.mp4	14.9 MB
05_continuous-valued-features.en.srt	8.8 KB
05_continuous-valued-features.en.txt	5.6 KB
05_continuous-valued-features.mp4	16.7 MB
06_regression-trees-optional.en.srt	12.5 KB
06_regression-trees-optional.en.txt	7.9 KB
06_regression-trees-optional.mp4	19.8 MB
/.../03_tree-ensembles/
01_using-multiple-decision-trees.en.srt	6.6 KB
01_using-multiple-decision-trees.en.txt	3.5 KB
01_using-multiple-decision-trees.mp4	13.1 MB
02_sampling-with-replacement.en.srt	6.7 KB
02_sampling-with-replacement.en.txt	3.5 KB
02_sampling-with-replacement.mp4	15.0 MB
03_random-forest-algorithm.en.srt	9.0 KB
03_random-forest-algorithm.en.txt	5.7 KB
03_random-forest-algorithm.mp4	16.1 MB
04_xgboost.en.srt	9.6 KB
04_xgboost.en.txt	6.2 KB
04_xgboost.mp4	22.1 MB
05_when-to-use-decision-trees.en.srt	10.7 KB
05_when-to-use-decision-trees.en.txt	5.7 KB
05_when-to-use-decision-trees.mp4	18.3 MB
/.../04_decision-trees/04_acknowledgments/
01_acknowledgements_instructions.html	4.9 KB
/Coursera - Advanced Learning Algorithms/
[CourseClub.Me].url	0.1 KB
/.../03_regression-model/
01_linear-regression-model-part-1.en.srt	0.0 KB
01_linear-regression-model-part-1.en.txt	0.0 KB
01_linear-regression-model-part-1.mp4	0.0 KB
02_linear-regression-model-part-2.en.srt	0.0 KB
02_linear-regression-model-part-2.en.txt	0.0 KB
02_linear-regression-model-part-2.mp4	0.0 KB
03_cost-function-formula.en.srt	0.0 KB
03_cost-function-formula.en.txt	0.0 KB
03_cost-function-formula.mp4	17.5 MB
04_cost-function-intuition.en.srt	0.0 KB
04_cost-function-intuition.en.txt	0.0 KB
04_cost-function-intuition.mp4	31.0 MB
05_visualizing-the-cost-function.en.srt	0.0 KB
05_visualizing-the-cost-function.en.txt	0.0 KB
05_visualizing-the-cost-function.mp4	0.0 KB
06_visualization-examples.en.srt	0.0 KB
06_visualization-examples.en.txt	0.0 KB
06_visualization-examples.mp4	18.0 MB
/.../04_train-the-model-with-gradient-descent/
01_gradient-descent.mp4	0.0 KB
04_learning-rate.en.srt	0.0 KB
04_learning-rate.en.txt	0.0 KB
04_learning-rate.mp4	0.0 KB
/.../01_multiple-linear-regression/
01_multiple-features.mp4	0.0 KB
/.../01_classification-with-logistic-regression/
01_motivations.en.srt	13.0 KB
01_motivations.en.txt	8.0 KB
01_motivations.mp4	22.0 MB
02_logistic-regression.en.srt	0.0 KB
02_logistic-regression.en.txt	0.0 KB
02_logistic-regression.mp4	0.0 KB
03_decision-boundary.en.srt	0.0 KB
03_decision-boundary.en.txt	0.0 KB
03_decision-boundary.mp4	19.9 MB
/.../03_gradient-descent-for-logistic-regression/
01_gradient-descent-implementation.mp4	0.0 KB
/.../04_the-problem-of-overfitting/
01_the-problem-of-overfitting.en.srt	18.8 KB
01_the-problem-of-overfitting.en.txt	9.8 KB
01_the-problem-of-overfitting.mp4	25.1 MB
02_addressing-overfitting.en.srt	13.2 KB
02_addressing-overfitting.en.txt	7.0 KB
02_addressing-overfitting.mp4	16.5 MB
03_cost-function-with-regularization.en.srt	0.0 KB
03_cost-function-with-regularization.en.txt	0.0 KB
03_cost-function-with-regularization.mp4	0.0 KB
04_regularized-linear-regression.en.srt	0.0 KB
04_regularized-linear-regression.en.txt	0.0 KB
04_regularized-linear-regression.mp4	20.8 MB
05_regularized-logistic-regression.en.srt	0.0 KB
05_regularized-logistic-regression.en.txt	0.0 KB
05_regularized-logistic-regression.mp4	21.8 MB
/.../03_week-3-classification/05_acknowledgments/
01_acknowledgments_instructions.html	4.7 KB
/Coursera - Supervised Machine Learning Regression and Classification/
[CourseClub.Me].url	0.1 KB
/Week 1/betaversion/
C1_W1_Lab01_Python_Jupyter_Soln.ipynb	4.1 KB
C1_W1_Lab02_Course_Preview_Soln.ipynb	0.6 KB
C1_W1_Lab03_Model_Representation_Soln.ipynb	13.2 KB
C1_W1_Lab04_Cost_function_Soln.ipynb	9.9 KB
C1_W1_Lab05_Gradient_Descent_Soln.ipynb	20.6 KB
lab_utils_common.py	3.3 KB
lab_utils_uni.py	14.5 KB
/Week 1/betaversion/images/
C1W1L1_Markdown.PNG	32.0 KB
C1W1L1_Run.PNG	7.3 KB
C1W1L1_Tour.PNG	8.9 KB
C1_W1_L3_S1_Lecture_b.png	84.8 KB
C1_W1_L3_S1_model.png	77.4 KB
C1_W1_L3_S1_trainingdata.png	88.3 KB
C1_W1_L3_S2_Lecture_b.png	136.5 KB
C1_W1_L4_S1_Lecture_GD.png	92.9 KB
C1_W1_Lab02_GoalOfRegression.PNG	107.7 KB
C1_W1_Lab03_alpha_too_big.PNG	61.4 KB
C1_W1_Lab03_lecture_learningrate.PNG	85.6 KB
C1_W1_Lab03_lecture_slopes.PNG	69.1 KB
/Week 1/
C1_W1_Lab01_Python_Jupyter_Soln.ipynb	4.1 KB
C1_W1_Lab02_Course_Preview_Soln.ipynb	0.6 KB
C1_W1_Lab03_Model_Representation_Soln.ipynb	50.4 KB
C1_W1_Lab04_Cost_function_Soln.ipynb	9.9 KB
C1_W1_Lab05_Gradient_Descent_Soln.ipynb	19.9 KB
data.txt	0.7 KB
deeplearning.mplstyle	4.9 KB
lab_utils_common.py	3.3 KB
lab_utils_uni.py	14.5 KB
/Week 1/images/
C1W1L1_Markdown.PNG	32.0 KB
C1W1L1_Run.PNG	7.3 KB
C1W1L1_Tour.PNG	8.9 KB
C1_W1_L3_S1_Lecture_b.png	84.8 KB
C1_W1_L3_S1_model.png	77.4 KB
C1_W1_L3_S1_trainingdata.png	88.3 KB
C1_W1_L3_S2_Lecture_b.png	136.5 KB
C1_W1_L4_S1_Lecture_GD.png	92.9 KB
C1_W1_Lab02_GoalOfRegression.PNG	107.7 KB
C1_W1_Lab03_alpha_too_big.PNG	61.4 KB
C1_W1_Lab03_lecture_learningrate.PNG	85.6 KB
C1_W1_Lab03_lecture_slopes.PNG	69.1 KB
/Week 1/__pycache__/
lab_utils_common.cpython-37.pyc	3.2 KB
lab_utils_uni.cpython-37.pyc	12.5 KB
/Week 2/archive/
C1_W2_Lab01_Python_Numpy_Vectorization_Soln-Copy1.ipynb	25.5 KB
/Week 2/
C1_W2_Lab01_Python_Numpy_Vectorization_Soln.ipynb	25.5 KB
C1_W2_Lab02_Multiple_Variable_Soln.ipynb	60.0 KB
C1_W2_Lab03_Feature_Scaling_and_Learning_Rate_Soln.ipynb	26.2 KB
C1_W2_Lab04_FeatEng_PolyReg_Soln.ipynb	12.4 KB
C1_W2_Lab05_Sklearn_GD_Soln.ipynb	6.4 KB
C1_W2_Lab06_Sklearn_Normal_Soln.ipynb	6.9 KB
deeplearning.mplstyle	4.9 KB
lab_utils_common.py	3.3 KB
lab_utils_multi.py	21.3 KB
/Week 2/data/
houses.txt	12.5 KB
/Week 2/images/
C1_W2_L1_S1_Lecture_b.png	84.8 KB
C1_W2_L1_S1_model.png	77.4 KB
C1_W2_L1_S1_trainingdata.png	88.3 KB
C1_W2_L1_S2_Lectureb.png	136.5 KB
C1_W2_L2_S1_Lecture_GD.png	92.9 KB
C1_W2_Lab02_GoalOfRegression.PNG	107.7 KB
C1_W2_Lab03_alpha_to_big.PNG	61.4 KB
C1_W2_Lab03_lecture_learningrate.PNG	85.6 KB
C1_W2_Lab03_lecture_slopes.PNG	69.1 KB
C1_W2_Lab04_dot_notrans.gif	1.7 MB
C1_W2_Lab04_Figures And animations.pptx	238.3 KB
C1_W2_Lab04_Matrices.PNG	14.1 KB
C1_W2_Lab04_Vectors.PNG	6.0 KB
C1_W2_Lab06_contours.PNG	38.0 KB
C1_W2_Lab06_featurescalingheader.PNG	70.2 KB
C1_W2_Lab06_learningrate.PNG	77.6 KB
C1_W2_Lab06_LongRun.PNG	309.2 KB
C1_W2_Lab06_scale.PNG	66.4 KB
C1_W2_Lab06_ShortRun.PNG	371.9 KB
C1_W2_Lab07_FeatureEngLecture.PNG	95.4 KB
/Week 2/__pycache__/
lab_utils_common.cpython-37.pyc	3.2 KB
lab_utils_multi.cpython-37.pyc	18.0 KB
lab_utils_uni.cpython-37.pyc	25.0 KB
/Week 3/archive/
C1_W3_Lab05_Cost_Function_Soln-Copy1.ipynb	8.5 KB
C1_W3_Lab05_Cost_Function_Soln-Copy2.ipynb	8.5 KB
C1_W3_Lab09_Regularization_Soln-Copy1.ipynb	18.4 KB
/Week 3/
C1_W3_Lab01_Classification_Soln.ipynb	131.2 KB
C1_W3_Lab02_Sigmoid_function_Soln.ipynb	8.4 KB
C1_W3_Lab03_Decision_Boundary_Soln.ipynb	35.5 KB
C1_W3_Lab04_LogisticLoss_Soln.ipynb	11.1 KB
C1_W3_Lab05_Cost_Function_Soln.ipynb	8.6 KB
C1_W3_Lab06_Gradient_Descent_Soln.ipynb	13.8 KB
C1_W3_Lab07_Scikit_Learn_Soln.ipynb	2.7 KB
C1_W3_Lab08_Overfitting_Soln.ipynb	3.5 KB
C1_W3_Lab09_Regularization_Soln.ipynb	18.4 KB
deeplearning.mplstyle	4.9 KB
lab_utils_common.py	11.6 KB
plt_logistic_loss.py	7.2 KB
plt_one_addpt_onclick.py	8.0 KB
plt_overfit.py	15.7 KB
plt_quad_logistic.py	13.0 KB
/Week 3/images/
C1W3_boundary.PNG	25.0 KB
C1W3_example2.PNG	26.4 KB
C1W3_mcpredict.PNG	29.6 KB
C1W3_trainvpredict.PNG	279.7 KB
C1W3_XW.PNG	8.9 KB
C1_W3_Classification.png	44.4 KB
C1_W3_Lab07_overfitting.PNG	26.9 KB
C1_W3_LinearCostRegularized.png	54.2 KB
C1_W3_LinearGradientRegularized.png	53.9 KB
C1_W3_LogisticCostRegularized.png	47.7 KB
C1_W3_LogisticGradientRegularized.png	51.2 KB
C1_W3_LogisticLoss_a.png	45.4 KB
C1_W3_LogisticLoss_b.png	50.3 KB
C1_W3_LogisticLoss_c.png	35.7 KB
C1_W3_LogisticRegression.png	39.0 KB
C1_W3_LogisticRegression_left.png	24.6 KB
C1_W3_LogisticRegression_right.png	22.4 KB
C1_W3_Logistic_gradient_descent.png	43.7 KB
C1_W3_Overfitting_a.png	33.3 KB
C1_W3_Overfitting_b.png	39.0 KB
C1_W3_Overfitting_c.png	34.9 KB
C1_W3_SqErrorVsLogistic.png	53.4 KB
/Week 3/pre_414/
C1_W3_Lab01_Sigmoid_function.ipynb	5.9 KB
C1_W3_Lab02_Decision_Boundary.ipynb	7.3 KB
C1_W3_Lab03_Cost_Function.ipynb	11.9 KB
C1_W3_Lab04_Gradient_Descent.ipynb	10.3 KB
C1_W3_Lab05_One_Vs_All.ipynb	0.9 KB
C1_W3_Lab06_Regularized_Cost.ipynb	0.6 KB
C1_W3_Lab07_Regularized_Gradient_Descent.ipynb	0.6 KB
C1_W3_Lab08_Scikit_Learn.ipynb	3.2 KB
lab_utils.py	0.7 KB
/Week 3/__pycache__/
lab_utils_common.cpython-37.pyc	9.2 KB
plt_logistic_loss.cpython-37.pyc	6.1 KB
plt_logistic_loss_Copy1.cpython-37.pyc	6.2 KB
plt_one_addpt_onclick.cpython-37.pyc	6.6 KB
plt_overfit.cpython-37.pyc	12.2 KB
plt_quad_logistic.cpython-37.pyc	11.5 KB
/Coursera - Supervised Machine Learning Regression and Classification 2022-6 Extras/
[CourseClub.Me].url	0.1 KB
/.../01_welcome-to-the-course/
01_welcome.en.srt	5.6 KB
01_welcome.en.txt	2.9 KB
01_welcome.mp4	8.9 MB
/.../01_unsupervised-learning/02_clustering/
01_what-is-clustering.en.srt	6.7 KB
01_what-is-clustering.en.txt	3.6 KB
01_what-is-clustering.mp4	9.2 MB
02_k-means-intuition.en.srt	11.0 KB
02_k-means-intuition.en.txt	5.8 KB
02_k-means-intuition.mp4	13.0 MB
03_k-means-algorithm.en.srt	15.1 KB
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03_k-means-algorithm.mp4	20.7 MB
04_optimization-objective.en.srt	14.4 KB
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04_optimization-objective.mp4	30.9 MB
05_initializing-k-means.en.srt	11.0 KB
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05_initializing-k-means.mp4	18.7 MB
06_choosing-the-number-of-clusters.en.srt	12.0 KB
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06_choosing-the-number-of-clusters.mp4	18.8 MB
/.../03_practice-quiz-clustering/
01_clustering_exam.html	5.7 KB
/.../04_anomaly-detection/
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01_finding-unusual-events.en.txt	9.9 KB
01_finding-unusual-events.mp4	27.0 MB
02_gaussian-normal-distribution.en.srt	15.3 KB
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03_anomaly-detection-algorithm.en.srt	16.4 KB
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06_choosing-what-features-to-use.mp4	33.5 MB
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01_making-recommendations.en.srt	8.9 KB
01_making-recommendations.en.txt	4.7 KB
01_making-recommendations.mp4	21.4 MB
02_using-per-item-features.en.srt	17.0 KB
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03_collaborative-filtering-algorithm.en.srt	0.0 KB
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/.../01_reinforcement-learning-introduction/
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/.../05_continuous-state-spaces/
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03_learning-the-state-value-function.mp4	0.0 KB
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/.../07_summary-and-thank-you/
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01_summary-and-thank-you.en.txt	2.9 KB
01_summary-and-thank-you.mp4	14.6 MB
/.../03_reinforcement-learning/08_acknowledgments/
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/Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/
[CourseClub.Me].url	0.1 KB
/
[CourseClub.Me].url	0.1 KB
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